This study explores the perspectives and practices of architects regarding the reuse of wood in construction across five South-Central European countries: Slovenia, Serbia, North Macedonia, Bosnia and Herzegovina (BiH), and Montenegro. Based on a survey of architectural professionals, the research explores their attitudes, challenges, and motivations for using reclaimed wood, with a focus on circular construction principles. Key findings reveal unanimous agreement among re-spondents that both their profession and government entities inadequately support or promote wood reuse within the context of circular construction. While architects value reclaimed wood, there are country-specific variations. Environmental benefits, unique aesthetics, historical value, and sustainability are cited as primary motivators for reclaimed wood use. Additionally, re-spondents emphasize the ecological aspect as the most important consideration in wood product reuse, followed by economic and technological factors. Common concerns revolve around the long-term quality and maintenance of wood products. This research provides insights into the challenges and opportunities surrounding reclaimed wood use in South-Central Europe, high-lighting the need for support mechanisms and increased awareness to advance circular construc-tion practices in the region. These findings can have implications for architects and investors by identifying market opportunities, promoting eco-friendly practices, and providing valuable in-sights for future building designs with a focus on reclaimed wood elements within circular con-struction.

This study focuses on the increased risk of high heat release and asphyxiation (toxic gas poisoning) in the event of a fire of polyurethane (PU) and MDF-based building materials, which are commonly used in building fires. Among them, polyurethane (PU) building materials are essential for buildings except in Europe and some other countries due to their excellent thermal insulation performance, but problems of short-term heat release and spread of toxic gases in the event of a fire continue to occur. To overcome these problems, researchers are actively working on introducing various flame retardants into building materials. Therefore, in this study, we produced a laboratory-sized (500mm*500mm) plate flame retardant board that can be utilized as a building material with a lower heat release rate and a lower toxicity index by mixing expanded graphite and ceramic binder as flame retardants in a main material based on the cellulose of waste paper by replacing the existing building materials with a hot-press method. According to the ISO-5660-1 test on the heat release rate of the plate flame retardant board, the THR value was 2.9 (MJ/m2) for 10 minutes, showing an effect of reducing the THR value by 36.3 (MJ/m2) compared to the THR value of 39.2 (MJ/m2) of the specimen made using only paper. In addition, the toxicity index of the flame retardant board was checked through the NES 713 test. As a result, the test specimen showed a toxicity index of 0.7, which is 2.4 lower than the toxicity index of 3.1 of MDF, which is utilized as a conventional building material. Based on the results of this study, the cellulose fire retardant board showed the effect of reducing the heat release rate and toxicity index of building materials in a building fire, which reduces the risk of rapid heat spread and smoke toxicity. This has the potential to improve the evacuation time (A-SET) of evacuees in fires. It is also important to show that recycling waste paper and utilizing it as the main material for building materials can be an alternative in terms of sustainable development.

Recreational and leisure areas play a special role. These areas mitigate or eliminate the disadvantages of living in large cities, and they enhance the quality of life in small towns. The aim of this study was to analyze the share of recreational and leisure areas in Polish counties in 2022. In Poland, recreational and leisure areas constitute a separate land-use category in cadastral registers. Annual cadastral data from the Land and Building Register at county level (in tabular form) were the main source of data for the study. The analysis revealed that the share of recreational and leisure areas was higher in counties situated in western and south-western Poland, as well as in cities. The spatially varied influence of socioeconomic factors on the share of recreational and leisure areas in Polish counties in 2002 was determined with the use of local Moran's I statistic and geographically weighted regression (GWR). The study confirmed that population density was significantly related to the share of recreational and leisure areas in Polish counties. The impact of the remaining socioeconomic factors associated with spatial and economic development varied across regions. The study also revealed that in addition to the current socioeconomic determinants, the share of recreational and leisure areas in Polish counties was also influenced by historical factors and the counties' development since their establishment.

Intermolecular interactions are the fabrics underlying almost all processes in living organisms, where two cornerstone concepts, intermolecular binding affinity (K d ) and binding energy (ΔG), have long been established to physically describe the strengths of biomolecular interactions, e.g., drug-target K d and ΔG to describe the strength of drug-target interaction. The past two-three years saw a big step forward in the use of artificial intelligence (AI) in structural biology (e.g., AlphaFold for protein structure prediction) and drug discovery & design. In light of the roles of K d and ΔG in drug discovery & design, the speed of this AI progress raises a question of what’s next for its practical application in the pharmaceutical industry, in addition to a system-wide account of biomolecular structures and motions. Last August, the concept of a general intermolecular binding affinity calculator (GIBAC) was for the first time coined and proposed in an MDPI-published preprint. Here, this article puts forward an updated conceptual and practical framework of GIBAC, including its inception, definition, construction, practical applications, technical challenges and limitations, and future directions. Moreover, this article argues that the time is now ripe for the construction of such an accurate, precise and efficient GIBAC to be on the agenda of the entire drug discovery & design community, to ensure its applicability & reliability, and to enhance its value in drug R&D in future.

The utilization and engineering of thermo-optic effects have found broad applications in integrated photonic devices, facilitating efficient light manipulation to achieve various functionalities. Here, we perform both an experimental characterization and theoretical analysis of these effects in integrated micro-ring resonators in high index doped silica (HIDS), which has had many applications in integrated photonics and nonlinear optics. By fitting the experimental results with theory, we obtain fundamental parameters that characterize their thermo-optic performance, including the thermo-optic coefficient, the efficiency for the optically induced thermo-optic process, and the thermal conductivity. The characteristics of these parameters are compared to those of other materials commonly used for integrated photonic platforms, such as silicon, silicon nitride, and silica. These results offer a comprehensive insight into the thermo-optic properties of HIDS based devices. Understanding these properties is essential for efficiently controlling and engineering them in many practical applications.

The paper shows that it is possible to obtain reliable information on the dependence of radial distribution of longitudinal birefringence in glass cylindrical elements with radial distribution of refractive index (GRIN lenses) on the basis of transverse polarization tomography data of residual stresses. This does not require complicated procedures of sample preparation, as is necessary in the case of longitudinal translucency measurements. The approach developed was verified in the experiments with a set of different GRIN lenses formed with ion exchange technique, and the closeness of the data obtained from transversal and conventional longitudinal transmission measurements was demonstrated.

Building situated in the flow path of wind is subjected to differential velocity and pressure distribution around the building envelope. Wind effects are influenced and vary for each individual shape of the tall building. Tall building structures are considered as cantilever structures with fixed ends at the ground. Wind exponential velocity acting along the height of the building makes velocity and pressure distribution more complex as the height of the building structure increases. This study discussed the effect of wind on an irregular cross-section shape. The study was conducted numerically with a building model placed in a virtual wind tunnel using the ANSYS (CFX) software tool. Wind effects are investigated on building model situated in a terrain category - II defined in IS: 875 (Part 3): 2015 wind scale model of 1:100 and turbulence intensity is 5 % and power law index α is considered as 0.143. Validation and verification of the study were made by comparing pressure coefficients on faces of a rectangular model of similar floor area and height as taken for a C-plan diamond-shaped model under similar boundary conditions, wind environment, and solver setting of numerical setup. The values of surface pressures generated on the recessed faces of the model and wind flow patterns within the recessed cavity were studied at wind incident angles 0°, 300, 60°, 1050, 1350 & 1800. The critical suction on all the recessed faces was observed to be at a 105° angle of wind attack.

The fourth industrial revolution has resulted in the digitalization of projects and operations across all sectors. Accordingly, efforts are being made to utilize advanced technologies to improve the energy efficiency of the building sector. This study has reviewed the current application and limitations of cutting-edge technologies in this regard. An overview of the use of the Internet of Things (IoT), artificial intelligence (AI), digital twin (DT), and building information modeling (BIM) for energy efficiency of buildings has been provided. It has been found that the use of Industry 4.0 technologies, during the construction and operational phase of buildings, has a great potential to reduce energy consumption and emissions of the sector. This study may help stakeholders of the built environment to understand the role of industry 4.0 tools for energy efficiency of the sector.

We discuss a remote sensing system that is used to simultaneously detect range-resolved differential absorption LIDAR (light detection and ranging; DIAL) signals and integrated path DIAL signals (IP-DIAL) from aerosol targets for ranges up to 22 km. The DIAL/IP-DIAL frequency converter consists of an OPO pumped at 1064 nm to produce light at 1.6 μm and operates at 100 Hz pulse repetition frequency. The probe light is free space coupled to a movable platform that contains one transmitter and two receiver telescopes. Hybrid photon counting/current systems increase the dynamic range for detection by two orders of magnitude. Range resolved and column integrated dry-air CO2 and CH4 mixing ratios are obtained from line shape fits of CO2 and CH4 centered at 1602.2 nm and 1645.5 nm, respectively and measured at 10 different frequencies over ≈ 1.5 cm-1 bandwidth. The signal-to-noise ratios (SNR) of the IP-DIAL returns from cloud aerosols approach 1000:1 and the uncertainties in the mixing ratios weighted according to the integrated counts over the cloud segments range from 0.1 % to 1 %. The range averaged DIAL mixing ratios are in good agreement with the IP-DIAL mixing ratios at the 1 % to 2 % level for both CO2 and CH4. These results can serve as a validation method for future active and passive satellite observational systems.

With the advent of digitization, the integration of advanced technologies in operations and projects across all sectors is in progress. Accordingly, efforts are being made to utilize cutting-edge technologies to improve the circularity of the built environment. This study aimed to review the existing applications and limitations of building information modeling (BIM) tools for circular economy (CE) implementation from this perspective. A literature review was conducted to provide an overview of the use of BIM tools for conducting life cycle assessments, energy analysis, waste management, and formulation of material passports for buildings. It was found that BIM tools, which are available across all life cycle phases of building, have a great potential to improve the circularity of the sector. The overview provided on the use of various BIM tools may help stakeholders of the built environment understand the role of BIM for CE adoption in the sector.

The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a computer data capture and visualization platform foundation for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design theory based on extensive data analysis. Additionally, the system presents information on occupants' behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human-machine communication and enabling timely adjustments to design strategies for new buildings and operation and maintenance strategies for existing buildings.

Nigeria's upstream oil and gas sector is extensively contributing to the economic growth of the country, but the sector is plagued with challenges around corporate social responsibility (CSR) and taxation practices. Petroleum Industry Act (PIA) is introduced to tackle these challenges towards promoting sustainable development in Nigeria. The aim of this study is to explore the PIA’s provisions on CSR and taxation, identify the Act’s implementation challenges and improvement opportunities, propose an integrated framework for monitoring and evaluating the PIA’s impact on CSR and taxation over time, and recommend measures for enhancing PIA’s impact on CSR and taxation support for sustainable development in Nigeria's upstream oil and gas sector. This study adopts the qualitative desk review method to analyze existent literature, reports, and documents regarding PIA’s provisions on CSR and taxation. Findings reveal that the PIA’s provisions greatly emphasize CSR initiatives and taxation transparency in improving responsible ethical business behaviour. An integrated framework for monitoring and evaluating PIA’s impact over time is developed. This study concludes that the PIA's provisions can balance CSR and taxation practices for sustainable development. The study’s recommendations include using the integrated framework as a structured strategy for monitoring and evaluating the PIA’s impact. This study contributes to the discussion on the imperatives of ethical business practices and regulatory frameworks for sustainable development drive in the oil and gas sector.

The hybridization of conventional thermal power plants by incorporation of renewable energy systems has witnessed widespread adoption in recent years. This trend aims not only to mitigate carbon emissions but also to enhance the overall efficiency and performance of these power generation facilities. However, calculating the performance of such intricate systems using fundamental thermodynamic equations proves to be both laborious and time-intensive. Nevertheless, possessing accurate and real-time insights into their performance is of utmost significance to ensure optimal plant operation, facilitate decision-making, and streamline power production planning. In this paper, we delve into the application of machine learning techniques, particularly hybrid methodologies, to predict the performance of power plants. Specifically, we employ three approaches: the Adaptive Neuro-Fuzzy Inference System (ANFIS), the ANFIS optimized via Particle Swarm Optimization (ANFIS-PSO), and the ANFIS optimized through Genetic Algorithm (ANFIS-GA). These techniques are alternatively applied to a complex hybrid thermal power plant, namely an Integrated Solar Combined Cycle Power Plant (ISCCPP). This ISCCPP comprises a steam turbine section, a gas turbine section, and a concentrated solar power system utilizing troughs as collectors. The energy transfer fluid, in conjunction with exhaust from the gas turbine section, heats water within a vessel or steam generator, producing steam to propel the steam turbine's rotor. Electricity generation is facilitated by both gas and steam turbines, which are coupled to a generator. The findings of this study underscore the accuracy and appropriateness of ANFIS-based models in evaluating and predicting the performance of intricate hybrid power plants. The ANFIS model exhibited an impressive overall coefficient of correlation of 0.9991. Notably, the integration of evolutionary algorithms (PSO and GA) into the ANFIS framework elevated model performance, yielding correlation coefficients of 0.9994 for ANFIS-PSO and 0.9997 for ANFIS-GA. It is noteworthy that ANFIS-GA demonstrated superior predictive capability. The modeling framework developed in this research offers valuable support to designers, energy managers, and decision-makers. It provides a robust and dependable tool to assess the performance of hybrid thermal power plants, which are poised for a global surge in numbers amid the ongoing energy transition.

There is a substantial lack of data relating to the hygrothermal traits of existing buildings and building materials. Moisture analysis in building envelopes is 1D (one-dimensional), and 2D and 3D effects and feedback can be neglected. Many European standards treat a moisture percentage in building envelopes as surface and interstitial moisture condensation, such as BS EN ISO 10211, BS EN ISO 13788, BS EN ISO 15148, and BS EN 15026. In this manuscript, there was a tendency to capture a relative quantity of superficial moisture, by metering spots on the inner and outer surface of wall lining systems with a moisture meter. The metering specimens were the buildings with different envelopes: a wooden hut-house, a masonry building and a building partially sheeted in stone. The referent heights on wall linings, for taking the moisture data were specified as 50 cm for a wooden and masonry building and 80 cm for a stone-sheeted building, from the ground. The obtained numeric results were palpable with no regard to the current state of the weather outside. The listed conclusions highlight the significance of a well-tailored building envelope, and its dependence on weather, junctions, gaskets, appropriate materials, etc.

Structural design optimization (SDO) plays a pivotal role in enhancing various aspects of construction projects, including design quality, cost-efficiency, safety, and structural reliability. Recent endeavors in academia and industry have sought to harness the potential of Building Information Modeling (BIM) and optimization algorithms to optimize SDO and improve design outcomes. This review paper aims to synthesize these efforts, shedding light on how SDO contributes to project coordination. Furthermore, the integration of sustainability considerations and the application of innovative technologies and optimization algorithms in SDO necessitate more interactive early-stage collaboration among project stakeholders. This study offers a comprehensive exploration of contemporary research in integrated SDO employing BIM and optimization algorithms. It commences with an exploratory investigation, employing both qualitative and quantitative analysis techniques following the PRISMA systematic review methodology. Subsequently, an open-ended opinion survey was conducted among construction industry professionals in Europe. This survey yields valuable insights into the coordination challenges and potential solutions arising from technological shifts and interoperability concerns associated with widespread SDO implementation. These preliminary steps of systematic review and industry survey furnish a robust knowledge foundation, enabling the proposal of an intelligent framework for automating early-stage sustainable structural design optimization (ESSDO) within the construction sector. The framework ESSDO addresses the challenges of fragmented collaboration between architects and structural engineers. This proposed framework seamlessly integrates with the BIM platform, i.e., Autodesk Revit for architects. It extracts crucial architectural data and transfers it to the structural design and analysis platform, i.e., Autodesk Robot Structural Analysis (RSA), for structural engineers via the visual programming tool Dynamo. Once the optimization occurs, optimal outcomes are visualized within BIM environments. This visualization elevates interactive collaborations between architects and engineers, facilitating automation throughout the workflow and smoother information exchange.

We present results of the detected voltage distribution of a quantum random number generator based on the photonic integration of semiconductor laser, delay interferometer and photodetector. We find that the integrated system behaves as expected for random number generation from gain-switched laser sources. The biggest advantage is that only electrical connections are needed to operate the system without the need for tricky and expensive optical alignment to external circuitry. We supply results showing that random bit stream created from the random numbers passes the NISTS statistical test suite tests; thus demonstrating the feasibility to generate random number via quantum means at gigabit/s rates from a single photonic integrated circuit. The results are backed by numerical simulations.

The benchmarking of hotel energy use comprehensively identifies the controllable and uncontrollable factors affecting energy performance, including building characteristics, management strategies, operations, and maintenance systems. Other factors include climatic conditions, floor areas, operating hours, occupancy rates, and guest populations. A benchmarking study on energy consumption patterns in significant hotels (each with less than 100 rooms and an average staff strength of 40 employees), situated in the university town of Nsukka (longitude 70 23' E, latitude 60 52' N), Nigeria, was performed using the data envelopment analysis (DEA) methodology. DEA, a linear programming technique that measures the relative performances of units, was chosen as a benchmarking methodology due to its ability to handle multiple inputs and outputs. Following a correlation test, energy use intensity, diesel consumption, and the number of employees were selected as the analysis inputs, while the occupancy rate was chosen as the output variable. Data on these variables spanning 12 months were collected using questionnaires, interviews, site visits, and oral conversations with hotel managers to ensure validity. Grid-supplied electricity accounted for most of the hotels' energy needs, followed by diesel used in generators. More than 70% of the electricity use was for HVAC. From the DEA, Hotel 3 (DMU H3) had a technical efficiency score of 1, whereas adjustments were recommended for improving the efficiency scores of the other hotels, which were deemed inefficient. DMU H7 had the lowest efficiency score (0.474) and the highest identified savings for electricity and diesel. The analysis also revealed that occupancy rates were generally low in the months of June and July, coinciding with the high rainfall season with its accompanying decline in outdoor activities. Consistent with this, electricity consumption was highest in the Christmas and Easter holiday months of December, January, and April following increased travel-related activities.

Germanium (Ge) nanostrip is embedded in polymer and studied as a waveguide. Measurement reveals that this new type of semiconductor/polymer heterogeneous waveguide exhibits strong absorption for the TE mode from 1500 nm to 2004 nm, while the propagation loss for the TM mode declines from 20.56 dB/cm at 1500 nm to 4.89 dB/cm at 2004 nm. The transmission characteristics serves as an essential tool to verify the optical parameters (n-κ) of the thin strips, addressing to the ambiguity raised by spectroscopic ellipsometry regarding highly absorbing materials. Furthermore, the observed strong absorption for the TE mode at 2004 nm is well beyond the cut-off wavelength of the crystalline bulk Ge (~1850 nm at room temperature). This redshift is modeled to manifest the narrowing of the Tauc-fitted bandgap due to the grain order effect in the amorphous Ge layer. The accurate measurement of the nanometer-scale light-absorbing strips in a waveguide form is a crucial step toward the accurate design of integrated photonic devices that utilize such components.

This paper proposes an active-reactive power collaborative scheduling model with cluster division for the flexible distributed energy resources (DERs) of smart building system to resolve the high complexity of centralized optimal scheduling of massive dispersed DERs in the distribution network. Specifically, the optimization objective of each cluster is to minimize the operational cost, the power loss cost, and penalty cost for the flexibility deficiency, and the second-order cone-based branch flow method is utilized to convert the power flow equations into the linearized cone constraints, reducing the nonlinearity and heavy computation burden of the scheduling model. Customized virtual battery models for the building-integrated flexible DERs are developed to aggregate the power characteristics of flexible resources while quantifying their regulation capacities with time-shifting power and energy boundaries. Moreover, a cluster division algorithm considering the module degree index based on the electrical distance and flexible balance contribution index is formulated for cluster division to achieve the information exchange and energy interaction in the distribution network with high proportion of building-integrated flexible DERs. Comparative studies have demonstrated the superior performance of the proposed methodology on the economic merits and voltage regulation.

Abstract: With the continuous integration of various energy systems and the reform of energy trading marketization, the traditional power demand response can no longer meet the needs of multi-energy coupling. For the joint response problem of multi-energy, this paper proposes a comprehensive demand response optimization incentive model considering the user response characteristics, with the complete energy service providers and multiple users as the participants of the comprehensive demand response, to solve the response strategy for the optimal goal of all parties. The implementation architecture of integrated demand response and the electrothermal energy hub model is introduced first. Secondly, the integrated demand response collaborative optimization strategy of the integrated energy service providers and users is established, and the existence and uniqueness of the optimal solution are proved. Finally, the example analysis demonstrates that the proposed strategy can reduce the integrated energy service providers' response cost and user dissatisfaction under multiple scenarios.

Buildings can play an important role in reducing GHG emissions through increased energy efficiency. The European Commission issued a proposal in 2021 suggesting that all new buildings should be “zero-emission Buildings” (ZEB), aiming at a zero GHG emission building stock by 2050.The extent to which ZEB can contribute to reduced GHG emissions, however, varies between countries, due to different energy systems. It is also important to consider other environmental effects to avoid that climate benefits come with unintended consequences.Here, we explore the life-cycle environmental performance for a ZEB in a case where electricity and heating is largely fossil-free. The assessment concentrates on i) environmental impact of the use stage in relation to the product stage, ii) the interrelation between different energy sources, with attention on household electricity, and iii) the performance for more impact categories than primary energy use and climate change. While our results generally support the use of ZEBs from an environmental perspective, they also show that the climate benefit in this setting is marginal. However, given that energy systems are connected and energy savings in one place can reduce the demand for fossil energy elsewhere, the climate benefit of ZEBs is likely underestimated. Besides methdological implications for future studies, this indicates that current EU policy is promising, as incentives for implementation of ZEBs is unaffected by domestic effects.

Building facade design plays an essential role in enhancing energy efficiency and reducing environmental impact in high-performance building design. Balancing the conflicts among various building facade design parameters to satisfy different optimization objectives constitutes a highly complex optimization problem. The rapidly increasing number of studies demonstrates a significant interest in implementing multi-objective optimization methods to tackle building facade optimization problems. This study conducts a systematic review of optimization methods for building facade optimization (BFO). The optimization objectives and design variables are categorized based on their characteristics. The efficiency and effectiveness of optimization algorithms in addressing BFO problems are compared. Building optimization techniques and tools are showcased, along with their functions and limitations. Key findings highlight the robust feasibility and effectiveness of optimization algorithms, methods, and techniques in resolving a diverse range of BFO challenges. The limitations, challenges, and future potential of these methods are summarized and proposed.

Matrix-variate Gaussian type or Wishart type distributions in the real domain are widely used in the literature. When the exponential trace has an arbitrary power and when a factor involving a determinant enters into the model or a matrix-variate gamma type or Wishart type model with exponential trace having an arbitrary power, is extremely difficult to handle. Evaluation of the normalizing constant in such a model is the most important part because when studying the properties of such a model, the method used in the evaluation of the normalizing constant will be the relevant steps in all the computations involved. One such model with a factor involving a trace and the exponential trace having an arbitrary power, in the real domain, is known in the literature as Kotz' model. No explicit evaluation of the normalizing constant in the model involving trace with an exponent and determinant with an exponent entering into the model and at the same time the exponential trace having an arbitrary exponent seems to be available in the literature. The normalizing constant widely used in the literature and interpreted as the normalizing constant in the general model and refers to as a Kotz' model does not seem to be correct. Corresponding model in the complex domain, with the correct normalizing constant, does not seem to be available in the literature. One of the main contributions in this paper is the matrix-variate distributions in the complex domain belonging to Gaussian type, gamma type, type-1 and type-2 beta type when the exponential trace has an arbitrary power. All these models are believed to be new. A second main contribution is the explicit evaluation of the the normalizing constants, in the real and complex domains especially in the complex domain, in a matrix-variate model involving a determinant and a trace as multiplicative factors and at the same time the exponential trace having an arbitrary power. Another main contribution is the introduction of matrix-variate models with exponential trace having an arbitrary exponent, in the categories of type-1 beta, type-2 beta and gamma distributions or in the family of Mathai's pathway models [1], both in the real and complex domains. Another new contribution is the logistic-based extensions of models in the real and complex domains with exponential trace having an arbitrary exponent and connecting to extended zeta functions introduced by this author recently. Some properties of such models are indicated but not derived in detail in order to limit the size of the paper. The techniques and steps used at various stages in this paper will be highly useful for people working in multivariate statistical analysis as well as people applying such models in engineering problems, communication theory, quantum physics and related areas, apart from statistical applications.

The efficiency success status of organization built environment assets management needs robust and comprehensive maintenance processes which depends on the efficiency of the contract information documents for the maintenance management within the assets life cycle and achieve positive return of the investments. Therefore, this paper highlights on the appropriate interactive approach to structuring information flow scope of the asset facilities management contract for construction projects based on GIS and BIM integration processes, sustainability standards, and As-built contractual documents of the project to support the organization owner and stakeholder to improve the asset management processes. Using expert interviews with comprehensive understand for the information type in several facility management contracts conducted in common Organization types based on reviewing available international facility management standards manual and contract of procedures for different services types, and required information flow inside international facility management firms. The study classify and build significant integrated information and data flow model contract drafting with measures and indicators of performance efficiency as guideline for monitoring, technically evaluating, and financially procedures for performance efficiency and quality of services provided in the facilities management contract for King Faisal University campus projects as a case study.

With the development of bioinspired green solutions for sustainable construction over the past two decades, bio-cementation, which exploits the naturally occurring phenomenon of calcium carbonate precipitation in different environments, has drawn a lot of attention in both building construction and soil stabilization. Various types of microorganisms, along with specific enzymes derived from these microorganisms, have been utilized to harness the benefits of bio-cementation. Different application methods for incorporating this mechanism into the production process of the construction material, as well as a variety of experimental techniques for characterizing the outcomes of bio-cementation, have been developed and tested. Despite the success of bio-cementation as a sustainable method to construction has been demonstrated in a significant body of literature at the laboratory scale, the expansion of this strategy to construction sites and field application remains a pending subject. The issue may be attributed to two primary challenges. Firstly, the complexity of the bio-cementation phenomenon is influenced by a variety of factors. Secondly, the extensive body of literature examines various types of microorganisms under different conditions, leading to a wide range of outcomes. Hence, this study aims to examine the recent advancements in utilizing the most commonly employed microorganism, Sporosarcina Pasteurii, to emphasize the significance of influential factors identified in the literature, discuss the findings that have been brought to light, and outline future research directions toward scaling up the process.

This paper reports aligned activities to promote energy and resource-efficient construction practice in Vietnam. First, the governance framework is introduced, including government decrees and technical standards. Then, a laboratory with building physics measurement technology is designed and partly set up at the local partner Vietnam Institute for Building Materials (VIBM), which can be used to determine the essential characteristic values required for the implementation of energy standards. The basis for the prioritization of the characteristic values are the requirements of the National technical regulation on energy efficient buildings of Vietnam – QCVN09:2017/BXD. Furthermore, basic characteristic values from international standards are described, which can also be used for calculations to optimize the energy consumption of buildings. In order to be able to carry out transient hygrothermal computer simulations, special characteristic values were also included. These are particularly useful for the research and development of new building materials and the evaluation of entire buildings in terms of thermal and moisture protection In order to communicate the material properties to the market and enable informed decision making by the stakeholders, a labeling system has been developed. Thereby, the practical means for implementing governance instruments are provided, and the related technical applications are supported.

Integrated cultivation strategies can significantly improve rice yield. However, it is unclear how integrated cultivation practices improve soil microbial diversity and its related mechanism in rice field. Therefore, four integrated cultivation practices i.e., no N application (N0), local farmers’ practice (FP), high-yield and high-efficiency practice (HYEY), and super-high-yield cultivation practice, impacts on soil properties and structure composition of microbial community were explored. Compared with N0, SHY treatment, significantly increased soil alkaline nitrogen and organic matter contents. HYHE and SHY treatments significantly altered soil fungal community and Alpha diversity. Based on Venn diagram analysis, the composition of bacterial communities under all treatments was similar, but with different compositions of fungal communities. Cluster analysis indicates that the Proteobacteria was the absolute dominant group of bacterial communities, and Chloroflexi, Bacteroidetes, and Acidobacteria were the dominant group. Different cultivation methods also led to changes in the main factors affecting soil bacteria and fungi composition. Available potassium and organic matter were the main environmental factors that affected bacteria, with the strong of available potassium on the soil. To sum up, SHY and HYEY were beneficial management options in terms of improved soil fertility Alpha diversity of the soil bacterial community respectively.

The integrated stress response is a signaling network comprised of four branches, each of which senses different cellular stressors, converging on the phosphorylation of eIF2α to depress global translation and initiate recovery. One of these branches is composed of GCN2, which senses cellular amino acid insufficiency and participates in the maintenance of amino acid homeostasis. Previous studies have shown that GCN2 is a viable cancer target when amino acid stress is provoked by inhibiting an additional target. In this light, we screened a combination of drugs to identify biologically active compounds which synergize with the GCN2 inhibitor TAP20. First, a panel of 25 compounds was assayed in six cancer cell lines for drug sensitivity. Each compound was then combined with TAP20 at concentrations below their IC50, and the impact on cell growth was assessed. Selected strongly synergistic combinations were further characterised using synergy analyses and matrix-dependent invasion assays. Inhibitors of proteostasis, of the MEK-ERK pathway and pan-CDK inhibitors flavopiridol and seliciclib were found to potently synergize with TAP20 in two of the tested cell lines. Among their common CDK targets is CDK7, which was selectively targeted with THZ-1 and found to synergize with TAP20. Finally, these combinations were found to be partially synergistic when assessed using matrix-dependent invasion assays. However, we found that TAP20 alone was sufficient to restrict invasion at concentrations well below its growth-inhibitory IC50. We conclude that GCN2 can be targeted for treating cancers by polytherapy or even monotherapy.

Τhe building automation control is a crucial factor for improving buildings energy efficiency and management, as well as improving the electricity grid's reliability indices. This paper presents the methodology, describes the necessary technology requirements and presents the decentralized building automation novel algorithm for Efficient demand side management in a building. All these are applied in an experimental university microgrid and the results are presented in terms of energy saving in kWh, money in € and working hours.

The physicochemical treatment/recovery techniques, including precipitation, membrane technology, solvent extraction, foam fractionation, adsorption, and aqueous two-phase systems, will be reviewed. The bio-treatment processes, based on microorganisms and/or enzymes consuming nutrients available in food-processing wastewater as low-cost substrates to produce valuable products, will be discussed in detail, including the production of microalga biomass in wastewater treatment systems. Finally, future research direction will be proposed to integrate the circular economy and develop integrated food processing wastewater management systems.

Cultivated Peanut (Arachis hypogaea L.) is an important oil and cash crop in worldwide. Hundred pod and seed weight are important components for peanut yield. In order to dissect the genetic control of hundred pod weight (HPW) and hundred seed weight (HSW), a RIL population containing 188 individuals was developed from a cross between Jihua 5 (JH5, large pod and seed size) and M130 (small pod and seed size). An integrated genetic linkage map was constructed by using SSR, AhTE, SRAP, TRAP and SNP markers. The map contained 3,130 genetic markers which were assigned to 20 chromosomes and covered 1,998.95 cM with an average distance 0.64 cM. Based on the genetic map, a total of 31 QTLs for HPW and HSW were identified on 7 chromosomes, explaining 3.7-10.8% of the phenotypic variation by each QTL. Among these, seven QTLs were detected under more than two environments, two major QTLs were found on B04 and B08, respectively. A QTL hotspot containing seven QTLs was detected on chromosome A08 spanning a 2.74 cM genetic interval with 0.36 Mb physical map which included 18 candidate genes. Among these, Arahy.D52S1Z, Arahy.IBM9RL, Arahy.W18Y25, Arahy.CPLC2W and Arahy.14EF4H may be involved in regulating peanut pod and seed weight. These results may help further analysis of genetic mechanisms for pod and seed size in cultivated peanut.

This paper presents a numerical study on the vertical (axial) and lateral (flexure) behavior of CFST (Concrete-Filled Steel Tube) columns with active hoop prestress; this transverse prestressing effect is achieved by bolting together two steel half-tubes. This study refers to new construction only (i.e., no retrofit). 12 prototype CFST column specimens (segments) are analyzed. These specimens differ in the prestressing force (3 levels) and in the gravity loading ratio (4 levels); they are selected to represent typical ground columns of mid-rise buildings. The structural behavior of these column specimens is simulated with a nonlinear model implemented in Abaqus; the concrete and steel behavior are described with a damage-plasticity and a plasticity model, respectively. Finally, the interface concrete-steel interaction is represented by a hard (compression-only) surface-to-surface contact model. The calculations involve three consecutive loading steps: (i) transverse prestress, (ii) axial force, and (iii) lateral loading (shear force and bending moment). The structural behavior of the CFST columns is deeply examined and discussed; the results show that their axial-flexural capacity is adequate. Noticeably, it is concluded that the overall benefits of prestressing the columns are only modest. Preliminary studies on the aforementioned mid-rise buildings equipped with the CFST columns show that their gravity and wind capacities are largely enough; conversely, their seismic capacity is sufficient for moderate seismic ground motions only.

In a saline semi-isolated Lagoon on the Cape Zeleny (White Sea), the annual dynamics of the vertical hydrological structure, and the seasonal dynamics of phytoplankton were traced, including species composition, and vertical distribution, abundance, nutrition type,and biomass.293 species and supraspecific taxa of algae and cyanobacteria were found. Most of the identified species are marine, and 38 species are freshwater. Taxonomic composition changed in the Lagoon during the year. Dinoflagellates dominated in winter and early June; unidentified cocci and flagellates in July; diatoms, dinoflagellates and unidentified cells in August; dinoflagellates in September; and unidentified cocci and flagellates in October–November. The abundance of algae also changed in the Lagoon during the year. The integrated biomass in the water column varied from 0.01 g C/m2 in January to 0.78 g C/m2 in early September. According to the abiotic parameters, the water column of the Lagoon is subdivided into several zones with different conditions and corresponding phytoplankton communities. Similarity between the communities of different horizons was 32-46% in summer and 7% in winter. The chemocline layer was the most populous. Almost the entire year it contained a maximum of phytoplankton biomass, 1-2 orders of magnitude higher than that in the overlying horizons. Comparison phytoplankton in the lagoon and in the nearby sea area was carried out. Despite the connection between the Lagoon and the sea phytoplankton structure in the surface water layer in the Lagoon and in the sea differs significantly in composition, quantitative parameters, and seasonal dynamics. The similarity of the communities in the sea and the Lagoon never exceeded 50%. In terms of biomass, the Lagoon lags behind the sea until mid-summer, but, starting from August, it outnumbers it, and the phytoplankton development in the Lagoon lasts longer, until late autumn. The phytoplankton structure and dynamics in the Lagoon and the sea by 24.5% was related to the daylight, water salinity, oxygen content and pH, but did not depend on water T, underwater illuminance, and depth. Oxygen content and pH are defined by PhP activity. Salinity serves as a vector of the vertical sequence of ecological niches. The daylight length seems to be the crucial factor of the seasonal PhP dynamics in the semi-isolated coastal stratified lakes and lagoons.

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.

The quest to comprehend the nature of consciousness has spurred the development of many theories that seek to explain its underlying mechanisms and account for its neural correlates. In this paper, I compare my own conscious electromagnetic information field (cemi field) theory with integrated information theory and global workspace theory for their ability to ‘carve nature at its joints’ in the sense of predicting the entities, structures, states and dynamics that are conventionally recognized as being conscious or nonconscious. I demonstrate the cemi field theory shares features with both integrated information theory and global workspace theory but consistently outperforms both by correctly predicting the entities, structures, states and dynamics that support consciousness. I argue that the simplest solution to the question of why cemi field theory consistently outperforms rival theories of consciousness is that the brain’s EM field is consciousness.

Climate change is expected to result in rising temperatures, leading to increased occurrences of extreme weather events like heat waves and cold spells. Urban planning responses are crucial for improving the adaptive capacity of cities and communities in dealing with significant temperature variations across seasons. This study aims to investigate the relationship between urban temperature fluctuations and urban morphology throughout the four seasons. Through quadrant and statistical analyses, the study identifies built-environment factors that contribute to moderate seasonal land surface temperatures (LST). The research focuses on Seoul, South Korea as a case study and calculates seasonal LST values at both the grid level (100m×100m) and street-block level, incorporating factors such as vegetation density, land use patterns, albedo, two- and three-dimensional building forms, and gravity indices for natural reserves. The quadrant analysis reveals spatial segregation between areas demonstrating high LST adaptability (cooler summers and warmer winters) and those displaying LST vulnerability (hotter summers and colder winters), with significant differences in vegetation and building forms. The spatial regression analysis demonstrates that higher vegetation density and proximity to water bodies play key roles in moderating LST, leading to cooler summers and warmer winters. Building characteristics have an invariant impact on LST across all seasons, where horizontal expansion contributes to higher LST, while vertical expansion reduces LST. These findings are consistent for both grid- and block-level analyses. The study emphasizes the flexible role of the natural environment in moderating temperatures.

In light of the current situation where no testing equipment is available for measuring thermal deformation of objects, this paper proposes a novel method for accurate and precise measurement. The method overcomes the limitations of previous approaches that relied on pitch angle. By utilizing the principle of biplane multiple reflections, a bivariate laser spot displacement analysis algorithm is devised to attain highly precise measurements of bivariate angles. Additionally, a temperature gradient comparison algorithm is introduced to calculate the indicator test results under specific temperature conditions. To validate the effectiveness and reliability of this method, a testing system is constructed and utilized. The results demonstrate that the thermal deformation angle change test achieves an impressive accuracy of 0.015″ and a rate of thermal deformation angle change of 0.3247″/°C. These values are in close agreement with the previously simulated analysis result of 0.359″/°C, with only a relative error of 9.55%. Therefore, the test results confirm the efficacy and reliability of this testing method along with the feasibility of the algorithm processing.

A healthy lifestyle and environmental protection play a big role in today's modern society. The production of organic wine, as with other organic commodities, is therefore increasingly popular with consumers. The selling price of organic wine is higher than that of wine that is not declared organic or BIO, so the question arises from consumers whether these wines contain more bioactive compounds and substances beneficial to the body. From a general point of view, it is known that grapevines contain a wide range of natural phenols and polyphenols. These substances affect the sensory properties of wines, especially color, and taste. The most of phenolic substances are found in red wines, slightly less in orange, and the lowest amounts are found in white wines. However, the representation of individual substances and their ratios differ based on the varieties and age of the wines. Therefore, this study aimed to compare the profile (chemical, physical and sensory) of organic wines compared to wines made from non-organic grapes, which are grown in a selected wine region - Kutná Hora. The analyzed wines were made from the same grape wine cultivar in the Kutná Hora area. The following analyzes were performed on the wine samples: the phenolic and antioxidant profile, the content of sulfites (free and total), alcohol, sugars, vitamins, density determination, and also sensory evaluation. The present study showed exact differences between samples of wines produced from the same cultivar, and same region, but declared as organic wines and wines from conventional production. Although a higher amount of bioactive substances is expected in wines from organic production, in most cases of presented analyzes, it did not show a statistically significant difference in the sense of a higher amount in BIO wines, on the contrary, in many cases the content of these substances was higher in wines from integrated production.

In spite of its remarkable characteristics, consciousness cannot be considered in splendid isolation. It is only one of the remarkable phenomena associated with the brain, the brain is just one of the organs in the body, and computers and brains share many characteristics as information-based systems. On the basis of the ubiquitous hierarchical organization of reality into stacked layers, and the particular importance of strong emergence in living systems, this article argues that the brain must also employ such methods to achieve its advanced functions. This is in line with the prop-osition of Integrated Information Theory (IIT) that consciousness requires a high degree of causal integration in its physical substrate. However, such emergence is also shown to underlie infor-mation processing in computers and the non-conscious functions of the brain. It is also demon-strated that both computers and brains exploit a specific type of information that is correlated to but not synonymous with states and mechanisms in the physical substrate. Emergent Information Theory (EIT) therefore presents consciousness as one member of a large and diverse family of non-physical but real forms of emergent information created by specific types of designed and evolved systems.

Bamboo is the building material of the past and future. It offers numerous properties that make it versatile for various applications, including construction. Its impressive strength-to-weight ratio enables it to bear substantial loads and stresses, while its good elasticity allows efficient energy absorption. However, its mechanical properties can vary based on factors such as species, age, locations, methods, and treatment. Treating bamboo is essential to enhance its properties and durability. The literature provides various natural and chemical treatments which enhanced some of the properties but also reported a drawbacks on higher temperature, content and duration. This paper reviewed 57 articles from Scopus database, specifically focusing on article-document type publications from the years 2003 to 2023. Additional references were also incorporated to address concerns in properties, treatment and standards to provide systematic understanding. MATLAB was utilized for data text analytics. With extensive assessment on the articles, the following gaps and concerns were observed and recommends for further study and assessment such as for bamboo properties, the development of centralized guidelines and procedures for the preparation and processing; exploration of alternative materials to reinforce bamboo without compromising its ductility; development of joint connections, and testing of mechanical properties considering seismic, wind and vibration. For treatment methods, the standardization of procedures using natural, chemical or combination. Lastly, for bamboo codes and standards, assessment of existing codes and standards for testing the mechanical properties of bamboo highlighting the potential limitations and areas, uniformity, differences with all existing similar standards. By filling these gaps, it can support the reliability and robustness of bamboo as a sustainable material, fostering its promotion and adoption in construction industry.

Although buildings constitute 35% of global energy use and 38% of carbon emissions from energy, the amount of energy and energy-related carbon emissions are increasing rapidly. On the other hand, non-renewable usable energy resources are decreasing on the contrary. New buildings are being built due to the increasing population and the existing building stock not meeting the needs or losing its lifespan. Some of the existing building stock is demolished and renewed for structural reasons and some for reasons such as usage performance. It is possible to reduce both energy consumption and greenhouse gas emissions with strategic energy uses in existing building stocks. There are various techniques to measure the maximum performance of sustainable and energy-efficient use of existing building stocks with which changes. Building Information Modeling (BIM) technology is one of these techniques that provides wide opportunities to users in recent years, and it is almost a virtual laboratory of structures. Building stocks can be modeled with BIM, and alternative shell and system suggestions can be used to measure how building performance has changed and to achieve the best results. In this research study, improvement scenarios that optimize energy use in existing building stocks are investigated on a sample residential building by using the virtual laboratory facilities of BIM. After measuring the current energy performance of the existing building with BIM tools, 192 alternative results were obtained with 6 variables (external walls, roof, insulation layers, transparent surface materials, lighting, and photovoltaic panels). The obtained alternatives were compared with the current state of the existing building. The material expenditures and amortization periods required for these alternative scenarios are also calculated. The results obtained were evaluated according to annual / lifetime energy consumption, fuel, electricity, initial investment costs, energy use intensity, and carbon emission amounts. With the optimization of the current situation of the sample building, annual fuel consumption decreased by 61% and electricity consumption by 64%. The amortization period of the optimum improvement was determined as 12 years.

The Covid-19 pandemic and the subsequent implementation of lockdown measures have significantly impacted global electricity consumption, necessitating accurate energy consumption forecasts for optimal energy generation and distribution during a pandemic. In this study, we propose a new forecasting model called the Multivariate Multilayered LSTM with Covid-19 case injection ($\proposedModel$) for improved energy forecast during the next occurrence of a similar pandemic. We utilize data from commercial buildings in Melbourne, Australia during the Covid-19 pandemic to predict energy consumption and evaluate the model's performance against commonly used methods such as LSTM, Bi-LSTM, Linear Regression, Support Vector Machine and the previously published work of Multilayered LSTM (M-LSTM). The proposed forecasting model was analyzed using the following metrics of mean percent absolute error (MPAE), normalized root mean square error (NRMSE), and $R^2$ score values. The model $\proposedModel$ demonstrates superior performance, achieving the lowest MPAE values of 0.061, 0.093, and 0.158 for data sets from 3 different buildings, respectively. Our results highlight the improved precision and accuracy of the model, providing valuable information for energy management and decision-making during the challenges posed by the occurrence of a pandemic like Covid-19 in the future.

eHealth applications are an essential component in achieving Universal Health Coverage. (1) Background: The lack of skilled healthcare personnel has hindered successful integration and use, especially in developing and low and middle-income countries. (2) Methods: A descriptive study was conducted using an online survey to collect quantitative data from 37 organizations to address this issue. (3) Results: The findings showed that there are limited training opportunities available for policymakers and eHealth specialists. Additionally, obstacles such as insufficient funds, inadequate infrastructure, poor leadership, and governance were identified and found to be context specific. To mitigate these challenges, the study proposed continuous in-service training, the implementation of computer-based systems, and the integration of academic modules. The importance of strong eHealth policies and committed leaders was also emphasized. (4) Conclusions: The results of this study support previous research and emphasize the importance of implementing practical and uncomplicated solutions to overcome eHealth barriers to capacity building in low- and middle-income countries. It is essential to recognize that the data collected for this study only pertains to BETTEReHEALTH.

The thermal properties of a building envelope are key indicators of the energy performance of the building. Therefore, methods are needed to determine quantities like U-values or heat capacitance in a fast, reliable way and with as little impact on the use of the building as possible. In this paper a technique is proposed that relies on a simplified electrical analogical model of building envelope components which can cover their dynamic thermal behavior. The parameters of this model are optimized to produce the best fit between simulated and measured outside surface temperatures. As the temperatures can be measured remotely with an infrared camera this approach requires significantly less installation effort and intrusion in the building than other methods. At the same time, a single measurement provides data for a large range of locations on a facade or a roof. The paper describes the method and a first experimental implementation of it. The experiment indicates that this method has the potential to produce results which have an accuracy that is comparable to standardized reference methods.

Building Information Modelling (BIM) methodology have been optimizing the construction activity in all sectors: multidisciplinary designs development; construction planning and monitoring; building management and maintenance. A BIM environment aggregates several disciplines and different skillsets and in order to control and improve the quality of a BIM project, a BIM manager is required. The BIM manager has the responsibility to coordinate all tasks involved in a building design and associated activities usually workout over the project documents. The professional can access to various discipline models, located in a shared board, and request for amendments if inconsistencies are detected. The present study issue is illustrated with three building cases were distinct specific projects, disciplines and tasks were elaborated: collaboration between disciplines (architecture, structures and construction); structural analyses and reinforcement details; quantity take-off of materials and cost estimation; construction scheduling and simulation. Although there are limitations in the implementation of BIM methodology in all sectors and stages, within the construction industry, BIM have been bringing an important improvement in the quality of a building design, reflected in the quality of the final product. BIM methodology is a current demand in the construction industry supported on advanced technology and in an adequate management of projects, were the BIM manager has an important role.

The emergence of Digital Twin (DT) technology is creating unique opportunities for human so-ciety in terms of real-time data transfer from the physical environment to its digital replica. DT technology has two-way interaction capabilities that enable data exchange between physical and virtual environments, creating bidirectional data flows. Progress has been made in different in-dustry sectors, but the Architecture, Engineering, Construction, and Operation (AECO) sector still requires further development. Recent studies have shown the potential for DT-based platform implementation in the lifecycle management of buildings and infrastructure. This paper examines the development and implementation of DT technology in the construction sector, identifying key definitions, enablers and use cases, while comparing its use with other industries and evaluating benefits and future potential.

Shape Memory Polymer (SMP) actuators are smart materials that adapt and switch shape in response to environmental conditions, allowing controlled and dynamic building systems. The integrated SMP strip enabled the adaptive facade shading system to operate independently and with flexibility under certain thermoresponsive conditions to regulate building performance. This study aims to improve adaptive façade performance in a hot-humid climate by determining optimal thermal activation factors for the shape memory polymer. This was achieved by comprehensively examining and analysing the impact of various SMP activation parameters on energy efficiency, thermal comfort, and visual comfort. In addition, dynamic IES-VE building energy simulation was used to evaluate the thermal performance of the adaptable facade. The results were validated using a multicriteria approach to compare with the existing glass façade of a high-rise apartment. The results showed that the coactivation technique, which combines solar radiation and air temperature triggers, proved to be the most efficient strategy to improve the performance of the adaptive façade. This strategy minimised heat gain, lowered indoor temperatures, reduced glare, and enhanced daylight comfort, resulting in notable energy savings through reduced cooling consumption. The study concluded that the utilisation of SMP actuators with fine-tuning activation parameters significantly optimised adaptive façade performance, promoting functionality, efficiency, and sustainability in buildings.

Digital-based differential amplifiers (DDA) are particularly suitable to low voltage digital integrated circuit technologies. This paper presents an exhaustive analysis of the digital-based analog amplifiers to take advantage of today's high-performance digital technologies and of computer-aided design (CAD) commonly employed to design integrated circuits. The operating principle and the main mathematical relations of the digital-based differential amplifiers are discussed along with an exhaustive explanation of its operating regions and of the corresponding power consumption. Finally, a detailed description of the design procedure of in UMC 180nm standard CMOS technology is shown.

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.

In Germany, as in many developed countries, over 60% of buildings were constructed before 1978, where most are in critical condition, requiring either demolition with plans for redevelopment or renovation and rehabilitation. Given the urgency of climate action and relevant sustainable development goals set by the United Nations, more attention must be shifted toward the various sustainability aspects when deciding on the strategy for renovation or redevelopment of existing buildings. To this end, this study focused on developing a smart decision support framework for aging buildings based on lifecycle sustainability considerations. The framework integrated digital technological advancements, such as building information modeling (BIM), point clouds processing with field information modeling (FIM)®, and structural optimization, together with life-cycle assessment to evaluate and rate the environmental impact of different solutions. Three sustainability aspects, namely, cost, energy consumption, and carbon emissions, were quantitatively evaluated and compared in two scenarios, namely, renovation, and demolition or deconstruction combined with redevelopment. A real building constructed in 1961 was the subject of the experiments to validate the framework. The result outlined the limitations and advantages of each method in terms of economics and environmental impact. It was further observed that optimizing the building design with the goal to reduce embodied energy and carbon in compliance with modern energy standards, was crucial to improve overall energy performance. This work demonstrated that the developed BIM-based framework to assess the environmental impact of rehabilitation work in aging buildings can provide effective ratings to guide decision-making in real-world projects.

Research background – Effective management of modern business is impossible without the systematic development and implementation of solutions aimed at changing it, due not only to market demands and competitive conditions, but also to the requirements of various social groups. Corporate governance should be focused on ensuring that all stakeholders perform their functions in the best possible way and satisfy their needs while maintaining a balance of interests between them.Purpose – This article is devoted to the consideration of the possibility of using the integrated business analysis developed by its author, based on a balanced scorecard, in the process of studying the strategic aspects of a company's activities.Design/methodology/approach – The methodological basis of the study was the concept of business analysis as such and the concept of a balanced scorecard by R. Kaplan and D. Norton.Findings – It is shown that an integrated business analysis based on a balanced scorecard involves a comparison with the target value, identifying the causes of deviations and predicting the company's strategic rating. It includes a comprehensive analysis of financial performance, customer performance, internal business process performance, and learning and development performance of a company's balanced system. Integrated business analysis based on a balanced scorecard begins with the analysis of the indicators of training and development of the company's personnel and ends with the forecasting of its strategic rating. His methodological tools are expert- score rating, comparison method, graphical and tabular methods, factor analysis techniques and various forecasting methods. Development of an integrated business analysis based on a balanced scorecard is the result of further development of the concepts of business analysis and a balanced scorecard and is aimed at further improving the information support of the strategic management of the company, ensuring its sustainable development in the long term.Originality/value – The author comes to the conclusion that integrated business analysis based on a balanced scorecard is a new and quite effective tool for studying the strategic aspects of a company's activities, forming the analytical support for its strategic management in modern conditions. Its results can be used in the development of management decisions not only long-term, but also medium-term and short-term, providing a sufficient degree of stability of the company from the point of view of its main stakeholders.

While human activities and climate change are threatening available natural ecosystems, targeted studies on the biological cycle, propagation, and cultivation of threatened species are crucial both for their conservation and sustainable exploitation. This study was designed to bridge extant research gaps regarding the vulnerable local endemic Campanula pelviformis, a wild edible green traditionally consumed in Crete (Greece) with agro-alimentary and medicinal interest as well as ornamental value. New knowledge was obtained on the abiotic environmental conditions prevailing in its wild habitats (natural distribution mapped in Geographical Information Systems and linked with open-source databases). We collected seeds from wild-growing populations (three lowland, two semi-mountainous), we tested their germination at four different temperatures (10, 15, 20 and 25oC) and under different light conditions (light/dark and darkness), and we performed fertilization trails [integrated nutrient management (INF), chemical fertilization (ChF), control] examining morphological and physiological characteristics, above- and below-ground macro- and micronutrients contents, as well as their phenol content and antioxidant capacity. There were population and temperature effects on seed germination and their interaction was statistically significant. Campanula pelviformis germinated better at 10 and 15 oC (>85% for all populations) with no preference on light conditions (98.75% and 95% in light and dark conditions). The INF application increased root dry mass, chlorophyll content index and chlorophyll fluorescence compared to other treatments and was beneficial for macro- and micronutrients concentrations in above-ground parts compared to previously studied wild-growing material, while below-ground parts were positively impacted by both fertilization types. Total phenols and antioxidant capacity were both increased by ChF fertilization. The data furnished herein led to the re-evaluation and upgrade of the feasibility and the readiness timescale for its sustainable exploitation in different economic sectors.

Species richness is a widely used measure for assessing the diversity of a particular area. However, observed richness often underestimates the true richness due to resource limitations, particularly in the small-sized sample or highly heterogeneous assemblage. Estimating species richness in a large-scale region typically involves an integrated data set consisting of subsamples collected independently from different subregions. However, the pooled sample of integrated data is no longer a random sample from the entire region, and the use of different sampling schemes results in variations in data formats. Consequently, employing a single sampling distribution to model the pooled sample becomes impractical, rendering existing richness estimators inadequate. This study theoretically explains the applicability of Chao's lower bound estimators in estimating species richness for large-scale areas using the pooled sample. Additionally, a new nonparametric estimator is introduced, which adjusts the bias of Chao's lower bound estimator by leveraging the Good-Turing frequency formula. This proposed estimator only utilizes the pooled sample's singleton, doubleton, and tripleton richness. Simulated data sets across various models are employed to demonstrate the statistical performance of the estimator, showcasing its ability to reduce bias and provide accurate 95% confidence intervals. Real data sets are also utilized to illustrate the practical application of the proposed approach.

A green, fast and selective approach for the synthesis of mono-substituted closo-decaborate derivatives [2-B10H9COR]n– has been established via a nucleophilic addition reaction between the carbonyl derivative of closo-decaborate [2-B10H9CO]– and the corresponding Grignard reagent RMgX, where R is the ethyl, iso-propyl, pentyl, allyl, vinyl, and propynyl groups. This approach is accomplished under mild conditions with 70–80% yields. The significance of these derivative is their ability to constitute building blocks for polymeric integration via the allyl, vinyl and propynyl substituents. All products were characterized by 11B, 1H, and 13C NMR, elemental analysis and mass spectrometry.

The building and construction sector has a significant impact on CO2 emissions and pollutants released into the atmosphere, which contribute to climate change. The EPDB Directive mandates the achievement of a minimum energy class E for all residential buildings by 2030 and an energy class D by 2033. Particularly, in Italy, about 86% of the existing building stock predates the enactment of any energy laws and regulations, making it imperative to apply the energy efficiency interventions. This paper provides a support decision tool for the identification of standardized interventions on the envelope, air conditioning system and domestic hot water production. The study is focused on a specific construction period class (1976 - 1990) in six different climatic zones. The methodological approach is based on a cataloguing phase and definition of Ante Operam energy classes, on the case study identification, the energy requalification interventions identification, solutions simulations, cost estimation. By simulating standardized interventions for each climatic zone, a range of possible combinations will be identified. The most advantageous ones will be determined based on a cost-benefit analysis, considering the potential class jump achieved. The research result is a matrix of energy efficiency interventions that is applicable to each climatic zone and can be extended to the existing housing stock.

The ubiquitous connectivity for the space-air-ground integrated network (SAGIN) of the beyond fifth generation of communication and sixth generation of communication (B5G/6G) is envisaged to meet the needs for the demanded quality of service (QoS), green communication, and "dual carbon" target. However, the offloading and computation of massive latency-sensitive tasks dramatically increases the energy consumption of the network. Furthermore, the traditional power supply technology of the network base stations (BSs) enhances the carbon emission. To address these issues, we first propose a SAGIN architecture with energy harvesting devices, where the BS is powered by both renewable energy (RE) and the conventional grid. The BS explores wireless power transfer (WPT) technology to power the unmanned aerial vehicle (UAV) for stable network operation. RE sharing between neighbouring BSs is designed to fully utilize RE for reduce carbon emission. Secondly, on the basis of task offloading decision, UAV trajectory, and RE sharing ratio, we construct cost functions with joint latency-oriented, energy consumption, and carbon emission. Then, we develop a twin delayed deep deterministic policy gradient (TD3PG) algorithm based on deep reinforcement learning to minimize the cost function. Finally, simulation results demonstrate that the proposed algorithm outperforms the benchmark algorithm in terms of reducing latency, energy saving, and lower carbon emission.

Standards are not only crucial for obtaining a certification for practical use, but also an essential guidance for inferring how and what to simulate as well test experimentally. This paper examines the potential applicability of existing standards from various domains, including aerospace and automotive, to Wing-Structure- Integrated high-pressure Hydrogen Tanks (SWITHs). It highlights the associated challenges and uncertainties, acknowledging the absence of a single, all-encompassing standard for SWITHs. We embark on an exploration aimed at identifying alternative standards that are best suited for SWITHs. The analysis scrutinizes existing standards that could potentially facilitate SWITH certification, with a particular focus on the inclusivity of externally loaded hydrogen tanks. Assessment criteria are established to filter standards that best meet the needs of SWITHs. Through this process, we identify two key standards that present themselves as the most promising alternatives. Moreover, we delineate the technical constraints involved in selecting the maximum nominal working pressure for high-pressure tanks intended for burst tests. Our findings reveal a current upper limit of 525 bar, imposed by the limitations of existing test facilities. The study underscores that these standards should serve as flexible guiding frameworks rather than rigid protocols, encouraging progressive development in the SWITH field.

Building Information Modelling (BIM) has gained significant relevance in civil engineering, particularly in the infrastructure sector. It offers the potential to increase efficiencies, optimize processes, and enhance sustainability throughout infrastructure projects’ life cycles. BIM consolidates information about asset components into a single model, enabling real-time updates, cost reduction, and improved consistency. Digital twins serve as valuable extensions of BIM in infrastructure, playing a crucial role during operation. By capturing real-time data from sensors and IoT devices, digital twins enabls continuous monitoring, proactive maintenance, efficient energy management, and informed decision-making for optimized operational efficiency. Advancements in 3D point cloud technologies, such as 3D laser scanning, have expanded BIM’s application in operation and maintenance. These technologies rapidly capture accurate and detailed three-dimensional information, prompting the exploration of automated alternatives to manual point cloud modeling. This paper demonstrates the application of supervised machine learning, specifically support vector machines, for analyzing and segmenting 3D point clouds, a crucial step in 3D modeling. Various approaches for semantic segmentation are introduced, investigated, and evaluated using diverse data sets. The results highlight the effectiveness of supervised machine learning techniques in achieving accurate segmentation of 3D point clouds.

Concentrator photovoltaic (CPV) technology offers an alternative to conventional photovoltaic systems, focusing on the concentration of solar radiation through the optics of the system onto smaller and more efficient solar cells. However, the surface on which the solar beam is incident must remain oriented towards the position of the sun, which requires the use of large and heavy external elements known as solar trackers. In addition to their size, these elements must be as accurate as possible to avoid misalignment. To avoid the need of these solar trackers, the concept of tracking-integrated concentrating systems has been developed. This technology has been researched to make CPV systems accessible in places where conventional systems are not viable, such as building roofs or agrivoltaic fields. This review presents a detailed classification of the existing designs in the literature and providing an overview of this type of system. By eliminating the need for external solar trackers, tracking-integrated CPV systems offer a promising solution to increase the adoption of this technology. Therefore, it is expected that these systems will be a viable and effective option for solar power generation.

In recent years, due to the low energy utilization of the whole life-cycle of buildings and the di-minished indoor and outdoor comfort of buildings and the impact on the surrounding environ-ment caused by the carbon emissions of the building life-cycle, the establishment of a whole life- cycle carbon emission model for buildings to improve their energy utilization at all stages of their life-cycle has received unprecedented attention. In China, the construction industry has become a major carbon emitter, and traditional houses, as a green development building type, are an effec-tive way to achieve carbon neutrality in buildings, but the existing green building evaluation system lacks quantitative indicators of carbon emissions in the building life-cycle. The exclusive evaluation indexes for regional and characteristic buildings, such as traditional houses, are ne-glected; This study explored the formula for calculating the life-cycle carbon emissions model of traditional residential houses under a carbon emission intervention and used real measurements of the physical environment and comparative analysis of the limitations of existing local stand-ards; The results showed that the carbon emission calculation formulas for each stage of the life-cycle of traditional residential houses must be established by combining the selection of local building materials, and the materials for sustainable energy and carbon sinks of green systems. Based on the results of indoor and outdoor heat and humidity environmental tests of residential houses and an analysis of the limitations of existing evaluation indexes due to locality, four im-portant factors affecting locality green buildings in terms of energy utilization, site ecology and landscape, land saving and material saving were extracted; on this basis, the whole life-cycle carbon emission model of traditional residential houses is constructed by combining the existing green building evaluation standards with the carbon emission indexes of the life-cycle of tradi-tional residential houses.

The implementation of grey and green infrastructure is an effective mean to address urban flooding and nonpoint source pollution, but due to the complexity of the process and the diver-sity of benefits, there is a lack of measurement for their comprehensive benefits. Adopting a typ-ical university in Beijing as an example, this paper simulated the multidimensional benefits of the water quantity, water quality, and ecology of grey and green facility renovation by coupling the storm water management model (SWMM) and InfoWorks Integrated Catchment Manage-ment (ICM). Monetization methods and economical means were employed to characterize the comprehensive benefits. The results showed that grey and green infrastructure retrofitting re-duces the number of severe overflow nodes in the study area by 54.35%, the total overflow vol-ume by 22.17%, and the nonpoint source pollution level by approximately 80% under the heavy rain scenario and 60% under the rainstorm scenario. The annual benefits of grey and green infra-structure renovation reached ¥765,600/year, of this amount, ¥83,100/year is from hydrological regulation, ¥454,100/year is from nonpoint source pollution reduction, and ¥228,300/year is from ecological improvement. The benefits of green facilities were higher than those of grey facilities, and the combined benefits were negatively correlated with the rainfall level, with a total bene-fit–cost ratio of 1.19. The results provide methodological and data support for grey and green in-frastructure retrofitting within the context of sponge cities.

With the popularization of intelligent sensing and the improvement of modern medical technology, intelligent medical sensing technology has emerged as the times require. This technology combines basic disciplines such as physics, mathematics, and materials with modern technologies such as semiconductors, integrated circuits, and artificial intelligence, and has become one of the most promising focuses in the medical field. The core of intelligent medical sensor technology is to make existing medical sensors intelligent, portable, and wearable with full consideration of ergonomics and sensor power consumption issues, for conforming to the current trends in cloud medicine, personalized medicine, and health monitoring. With the development of automation and intelligence in measurement and control systems, it is required that sensors have high accuracy, reliability, stability, as well as certain data processing capabilities, self-checking, self-calibration, and self-compensation，while traditional medical sensors cannot meet such requirements. In addition, in order to manufacture high-performance sensors, it is also difficult to improve the material process alone, and it is necessary to combine computer technology with sensor technology to make up for its performance shortcomings. Intelligent medical sensing technology combines medical sensors with microprocessors to produce powerful intelligent medical sensors. On the basis of the original sensor functions, intelligent medical sensors also have functions such as self-compensation, self-calibration, self-diagnosis, numerical processing, two-way communication, information storage, and digital output. This review focuses on the application of intelligent medical sensing technology in biomedical sensing detection from three aspects: physical sensor, chemical sensor, and biosensor.

Family Integrated Care (FICare) is associated with improved developmental outcomes and decreased parental mental health risks in stable preterm infants. However, less is known about its application in critically ill infants who are at greater risk for adverse outcomes. The objective of this study was to assess the safety and feasibility of implementation of FICare in critically ill infants in the first few weeks of life. In this prospective cohort study, 41 critically ill infants were enrolled: 17 in observational group receiving standard care (SC)and 24 in the FICare Plus group. Resources were developed for staff and parents to support earlier engagement in infant care. Outcomes were assessed using standardized questionnaires. The t-test or Wilcoxon Rank-Sum test were used to compare continuous variables, while Chi-square or Fisher exact test were used for categorical variables, respectively. Baseline maternal and infant characteristics were similar in both groups. The tools and procedures developed for FICare Plus successfully supported greater engagement in the care of their infant with no increase in adverse events and no increase in parent stress. Preliminary measures of infant efficacy were similar in both groups. Total anxiety scores were high among all parents at enrolment {83.1 (67-94) vs 77.3 (66-86); p-value 0.4}. However, the scores prior to discharge were lower in FICare Plus group {78 (71-90) vs 63 (52-74.5); p-value 0.02}. This pilot study showed that it is feasible and safe to implement family integrated care in critically ill infants.

Bollworm poses a significant threat to cotton crops worldwide, including in the Fergana province of Uzbekistan. This study aims to explore innovative approaches to bollworm control and contribute to the global understanding of integrated pest management strategies (IPM). Using an extensive literature review and field observations, the study evaluates the effectiveness of an integrated protection system in reducing reliance on chemical inputs while increasing overall efficiency. The results highlight the multigenerational life cycle of bollworm, its impact on various crops, and the need for artificial biological control methods and targeted insecticide applications. In addition, the study highlights the need to adopt globally accepted IPM practices to ensure sustainable pest management. The findings underscore the importance of collaboration among researchers, farmers, policymakers, and industry representatives in developing and implementing advanced control measures. Through integrated approaches and the incorporation of scientific advances, bollworm infestations can be contained while safeguarding agricultural productivity and minimizing environmental risks.

For Convolutional Neural Network (CNN), Depthwise Separable CNN (DSCNN) is a preferred architecture for Application Specific Integrated Circuit (ASIC) implementation on edge devices. It can benefit from a multi-mode approximate multiplier proposed in this work. The proposed approximate multiplier uses two 4-bit multiplication operations to implement a 12-bit multiplication operation by reusing the same multiplier array. With this approximate multiplier, sequential multiplication operations are pipelined in a modified DSCNN to fully utilize the PE array in the convolutional layer. This Approximate (A-DSCNN) was implemented on TSMC 40-nm CMOS process with a supply voltage of 0.9 V. At the clock frequency of 200 MHz, the design achieves 4.78 GOPs/mW while occupying 1.24 mm x 1.24 mm silicon area. Compared to conventional DSCNN implemented in a similar process node, the chip area and power consumption were reduced by 53% and 25%, while the throughput was improved by 17%.

This research paper examines the role of mass media in fostering positivity for the purpose of nation building. The mass media, including television, radio, print, and online platforms, holds significant influence over public opinion and societal attitudes. However, in recent years, there has been a growing concern about the predominance of negative news and content, which can have detrimental effects on the overall well-being of individuals and the development of a cohesive society. This study explores strategies and approaches to enhance positivity in mass media for the betterment of nations. It investigates the potential benefits, challenges, and ethical considerations associated with promoting positivity through various media channels. This paper provides recommendations for media organizations, policymakers, and society at large to cultivate a more positive media landscape that contributes to nation building.

Foliar fungal diseases in tomatoes include early blight (Alternaria linariae), Septoria leaf spot (Septoria lycopersici), and late blight (Phytophthora infestans) which is oomycetes. These are one of the significant production constraints in tomatoes. We describe the etiology, host range, distribution, symptoms, and disease cycle to understand the biology followed by management practices emphasizing the resistance breeding approach for these diseases. In crop improvement efforts, we provide an analytical review, including conventional and molecular methods for improving this disease resistance. Modern breeding tools, including genomics, genetic transformation, and genome editing, can be used to improve these traits. There is a good possibility of using these tools in the future to improve these traits.

We report a small footprint cost-effective isothermal rapid DNA amplification system, with integrated microfluidics for automated sample analysis and detection of SARS-CoV-2 in human and environmental samples. Our system measures low-level fluorescent signal in real-time during amplification, while maintaining the desired assay temperature, on a low power, portable system footprint. A unique soft microfluidic chip design was implemented to mitigate thermocapillary effects and facilitate optical alignment for automated image capture and signal analysis. The system-on-board prototype coupled with the LAMP primers designed by BioCoS, is sensitive enough to detect viral loads of SARS-CoV-2 in a broad concentration range corresponding to a threshold cycle range of 16 to 39. Clinical specimens were tested at Kingston Health Sciences using a clinically validated PCR assay and variants were determined using whole genome sequencing.

The Victorian Government Inquiry into wildfires that killed 173 people in 2009 has driven an Australian policy shift from self-evacuation or staying and defending a well-prepared property (‘go or stay’) to self-evacuation under catastrophic fire weather (‘leave early’). The Inquiry also led to the establishment of national ‘performance standards’ for Private Fire Shelters (PFS, that also known as bunkers). Nonetheless, incorporation of PFS into national bushfire policy remains embryonic with only Victoria having streamlined accreditation and planning approval processes. Arguments against PFS include potentially engendering complacency about preparing dwellings to survive fire and encourage risky behavior in response to a fire threat. Counteracting these arguments is research that shows that residents without PFS have low engagement with bushfire preparation and typically delay evacuation. In any case, because wildfire is unpredictable it is accepted that self-evacuation plans must have fallback positions that include sheltering ‘in place’ from the bushfire, making properly used and well maintained PFS an important element of bushfire safety. A less discussed barrier to PFS uptake outside Victoria appears to hinge on a lack of clarity about obligations for their design, certification, and consistency with planning approvals. The escalating Australian fire crisis demands much greater research and development in legal frameworks, policy and planning processes for PFS, as well as design and construction standards.

The construction industry has witnessed the increasing use of digital tools and smart solutions, particularly, in the realm of buildings energy automation within the concept of smart cities. While to truly realize the potential benefits of smart cities, a broader scope of smart initiatives is required to support the transition from smart buildings towards smart neighbourhoods, appreciated as the critical unit of urban development. To support this interplay of smart solutions between buildings and neighbourhoods, this article aims to collect and review all smart solutions presented in existing scientific articles, technical literature, and realized European projects. These solutions are classified under two main sections of buildings and neighbourhoods, which are investigated through five domains: buildings energy-related uses, renewable energy sources, water, waste, and open space management. Showcasing the quantitative outcomes demonstrates the potential benefits of implementing smart solutions from buildings to neighbourhoods. Moreover, this research concludes that the true enhancement of energy conservation goes beyond the buildings’ energy component and can be genuinely achieved by integrating intelligent elements of the neighbourhood, due to their strong interdependencies. Future research is recommended to focus on assessing the effectiveness of these solutions towards resource conservation.

This study proposes a framework to integrate Sustainability within Management Systems Standards and subsequently implement and disclose Sustainable Development goals and results. Moreover, it investigates the SD goals (SDGs) and results (SDRs) that Portuguese organizations with Integrated Management Systems (IMSs) disclose to their interest parties. The study, supported by content analysis, highlights that the four more frequently disclosed SDGs are “life on land“(50.0%), “industry, innovation, and infrastructure” (47.1%), “responsible consumption and production” (47.1%), and “partnerships for the goals” (47.1%). Conversely, the four SDRs most frequently disclosed are “employment” (82.4%), “economic performance” (79.4%), “anti-corruption” (64.7%), and “occupational health and safety” (61.8%). Hence, SDGs disclosure emphasizes the environmental dimension, while SDRs disclosure highlights the social dimension (economic dimension present in both SDGs and SDRs). Finally, the disclosure of SDGs and SDRs in institutional reports presents a positive and strong correlation that is statistically significant. Overall, the contributions of this research are twofold. First, it supports the integration of the SDGs within organizations, and second, it stimulates the demonstration of their impacts on the SDGs (the SDRs).

The response of structures under pulse-like ground motions is characterized by the large amount of energy input in a few cycles. Consequently, structures with insufficient strength may suffer severe damage owing to excessive deformation. In a previous paper, the energy-based prediction procedure for the peak and cumulative response of a reinforced concrete (RC) frame building with steel damper columns was proposed (Fujii and Shioda, 2023). Although this procedure was verified by comparison to the nonlinear time-history analysis (NTHA) results, the performance of the proposed procedure with pulse-like ground motion records has not been verified yet. In this study, the accuracy of the energy-based prediction procedure for an RC frame building with steel damper columns was investigated by considering pulse-like ground motions. The numerical analysis results reveal that the accuracy of the predicted peak response is satisfactory, which agrees with the results of the author’s previous study. However, the accuracy of the predicted total input energy to the building model depends on the ratio of the pulse period of the ground motion to the effective fundamental period of the building model. The reasons for this underestimation of the total input energy are discussed in this paper.

Climate change affects water resources through the decrease of rainfall and the increase in temperatures and evapotranspiration. An indirect impact of climate change is also the increase of water uses by human activities. In this review, 320 papers were retrieved, of which 134 spanning five continents impacts and solutions to be used to better understand the effects of climate change on water resources, ecosystems, human health, security and socio-economic aspects were selected. Here, suggestions and proposals by scientists from around the world towards solutions, tips and ideas to deal with climate change and the best solutions for future water management were presented. The main solutions highlighted concern integrated water resources management, political direction, policies, increase in knowledge and new technologies. Furthermore, most of the papers analyzed underline that water resources management needs to incorporate protection and restoration of ecosystems and their services. Nature-based solutions need to be the starting point of new scientific and innovative ways to deal with climate change and towards future climate adaptation. In this complex evolution of the water resource, where is the management of the water resource in Italy going?

Currently there are strong and sustained growth trends observed in multi-disciplinary industrial technologies such as building-integrated photovoltaics and agrivoltaics, where renewable energy production is featured in building envelopes of varying degrees of transparency. Novel glass products can provide a combination of thermal energy savings and solar energy harvesting, enabled by either patterned-semiconductor thin-film energy converters on glass substrates, or by using luminescent concentrator-type approaches to achieve high transparency. Significant progress has been demonstrated recently in building integrated solar windows featuring visible light transmission of up to 70%, with electric power outputs of up to Pmax ~ 30-33 Wp/m2. Several slightly different designs were tested during 2021-2023 in a greenhouse installation at Murdoch University in Perth, Western Australia. The objective of this paper is to report on the field performance of these PV windows in the context of agrivoltaics, and to provide some detail of the performance differences measured in several solar window designs related to their glazing structure materials. Methods for the identification and quantification of long-term field performance differences and energy generation trends in solar windows of marginally different design types are reported. The paper also aims to outline the practical application potential of these transparent construction materials in built environments, focussing on the measured renewable energy figures and seasonal trends observed during the long-term study.

In recent years, the need to make the built environment more resilient and adaptable to climate change has become increasingly evident. In Europe, this aspect concerns the vast majority of existing buildings, which present several deficiencies from the energy-efficiency point of view, considering they were designed before the introduction of modern energy codes. Nowadays, it is possible to retrofit existing buildings using advanced and high-efficient technologies such as Double Skin Façades (DSFs). The research aims to evaluate the use of properly designed DSFs for the energy restoration of existing buildings. In detail, various DSF configurations are applied to a residential building located in central Italy and investigated under present and future climate conditions, estimated through regional climate models. The results underline that all the analysed Double Skin Façades confirm to be a useful option, and, in particular, the Multi-Storey typology allows drastic energy needs decrement. Moreover, the general increase in temperatures and solar radiations could affect the building energy performance, and the insertion of DSF can mitigate the climate change effects, reducing the predicted energy consumption and ensuring better behaviours than the building in its original state.

As renewable energy generation prediction system has been introduced into the energy trading market, making a model to accurately predict the quantity of solar photovoltaic (PV) energy generation has become a significant problem. Moreover, to encourage an accurate prediction of the quantity of energy generation, an incentive system has been implemented for those who predict the quantity of solar PV energy under the error rate of 8%. Therefore, it has become more important to investigate and analyze current prediction technology numerically and develop more advanced prediction system. In this study, we tried to develop a better model to improve the accuracy of solar PV energy generation quantity by comparing three models made with gradient boosting machine (GBM), Model 1, Model 2, Model 3 respectively. Model 1 was built with the whole training data set without any additional preprocessing. After conducting some additional preprocessing procedure to predict solar energy generation more accurately, we made Model 2 with the whole training data set and Model 3 with only upper 10% of energy generation capacity. To compare the accuracy of three models, normalized mean absolute error (nMAE) was used as an evaluation index. The nMAE of Model 1 was 9.64% while the Model 2 showed 8.41%. Also, Model 3, which was constructed with the training set of upper 10% energy generation capacity, outperformed with the nMAE of 8.08%. For further study, to check the effectiveness of models constructed with GBM, a time series model, autoregressive integrated moving average (ARIMA), was also built and the nMAE was compared.

Vernacular architecture constitutes a rich source of information and ancestral knowledge that can become a key resource for sustainable development through its passive design strategies, which effectively respond to local climatic and weather conditions using locally sourced materials for the construction of its supporting structure and enveloping elements, as well as spatial organization and the incorporation of a buffer area (patio) that optimize the use of renewable resources. This qualitative study analyzes a traditional housing typology with a central patio located in the Historic Center of Azogues city, Ecuador, to evaluate its interior thermal comfort through in-situ monitoring in the different building spaces. Using the open-source software Open Studio and EnergyPlus, a simulation model was built to assess the annual thermal performance of the house. Field records were used to verify the effectiveness of the strategies that respond to the climatic conditions of the area. The analysis carried out on the passive strategies used in the selected house with regard to natural ventilation, solar protection, and thermal insulation, which depend on various aspects of the building, such as its location, internal space arrangement, design of openings (doors and windows), among others. The thermal simulations reveal that the traditional house located in the Historic Center of Azogues city is well adapted to the local climate, although interior thermal comfort is not entirely satisfactory.

The aim of this study is to propose and validate the state space mode decomposition technique for precise mode separation of non-classical damping systems and closely distributed modal systems. To assess the reliability and applicability of this technique, a 40-story building with a tuned mass damper is investigated, and acceleration responses measured by the building's health monitoring system are used for the verification of the technique. The mode separation results reveal that the separated modal power spectrum becomes distorted at neighboring natural frequency ranges when the performance index only considers the concentration of power spectral energy at the target natural frequency. However, by introducing an augmented performance index that includes a constraint condition to account for distortion, more accurate mode decomposition can be achieved.

Building outlines extracted from remote sensing images and raster maps often have irregular boundaries, redundant points, inaccurate positions, and unclear turns due to factors such as image quality, complexity of the surrounding environment, and extraction methods. This study proposes a regularization algorithm for right-angled polygon building outlines with jagged edges. First, the minimum bounding rectangle of the building outline is established and populated with a square grid based on the smallest visible length principle. An overlay analysis is then applied to the grid and original building to extract the turning points of the outline. Finally, the building orientation is used as a reference axis to sort the turning points and reconstruct the simplified building outline. Analysis of the experimental results shows that the proposed simplification method enhances the morphological characteristics of building outlines, such as parallelism and orthogonality, while considering simplification principles, such as the preservation of direction, position, area, and shape of the building. The proposed algorithm provides a new regularization method for building outlines with jagged edges.

This paper presents the design and implementation of a versatile IoT testbed utilizing the openHab platform along with various wireless interfaces, including Z-Wave, ZigBee, WiFi, 4G-LTE, and IR, and an array of sensors for motion, temperature, luminance, humidity, vibration, UV, and energy consumption. First, the testbed architecture, setup, basic testing, and collected data results are described. Then, by showcasing a typical day in the laboratory, we illustrate the testbed's potential through the collection and analysis of data from multiple sensors. The study also explores the capabilities of the openHab platform, including its robust persistence layer, event management, real-time monitoring, and customization. The significance of the testbed in enhancing data-collection methodologies for energy assets and unlocking new possibilities in the realm of IoT technologies is particularly highlighted.

The global demand for energy has been steadily increasing due to population growth, urbanization, and industrialization. Numerous researchers worldwide are striving to create precise forecasting models for predicting energy consumption to manage supply and demand effectively. In this research, a time-series forecasting model based on multivariate multilayered long short-term memory (LSTM) is proposed for forecasting energy consumption and tested using data obtained from commercial buildings in Melbourne, Australia: the Advanced Technologies Center, Advanced Manufacturing and Design Center, and Knox Innovation, Opportunity, and Sustainability Center buildings. This research specifically identifies the best forecasting method for subtropical conditions and evaluates its performance by comparing it with the most used methods at present, including LSTM, bidirectional LSTM, and linear regression. The proposed multivariate multilayered LSTM model was assessed by comparing mean average error (MAE), root-mean-square error (RMSE), and mean absolute percentage error (MAPE) values with and without labeled time. Results indicate that the proposed model exhibits optimal performance with improved precision and accuracy. Specifically, the proposed LSTM model achieved a decrease in MAE by 30%, RMSE by 25%, and MAPE by 20% compared to the LSTM method. Moreover, it outperformed the bidirectional LSTM method with a reduction in MAE by 10%, RMSE by 20%, and MAPE by 18%. Furthermore, the proposed model surpassed linear regression with a decrease in MAE by 2%, RMSE by 7%, and MAPE by 10%. These findings highlight the significant performance increase achieved by the proposed multivariate multilayered LSTM model in energy consumption forecasting.

Energy savings have been a major driver for improving building airtightness in the last period. Air infiltration has an important influence on energy efficiency and significantly influences the indoor air quality and pollutant distribution in residential buildings. Pressure difference lead to air permeability through the building envelope via cracks and un-controlled air leaks, which increase not only energy consumption, also cause noise from the outside and entering particles harmful to human health. Therefore, the issue of airtightness of the building envelope has been included in the standards and regulations. Building airtightness is influenced by various design parameters such as window/wall ratio, type of joinery, size of usage area, wall material and the insulation application also the quality of workmanship. In this study, the airtightness performance of 43 different residentials in Balıkesir was deter-mined by the BlowerDoor test measurement and in the context of airtightness the architectural design parameters impact was investigated. The air exchange rate (n50) values of 43 residences were obtained between 1.94 - 49.02 h-1 and compared with the existing standards. In addition, “usage area” was determined as the most effective parameter, followed by the size of the usage area, the transparency rate of the facades, the wall material type and the insulation status.

Urban spatial perception critically influences human behavior and emotional reactions, emphasizing the necessity of aligning urban spaces with human needs for enhanced urban living. However, functionality-based categorization of urban architecture is prone to biases, stemming from disparities between objective mapping and subjective perception. These biases can result in urban planning and designs that fail to cater adequately to the needs and preferences of city residents, negatively impacting their quality of life and the city's overall functionality. In this study, we apply machine learning to elucidate these biases within urban spatial perception research, utilizing a three-step methodology: objective mapping, subjective perception analysis, and perception deviation assessment. Our findings reveal that machine learning can expose hidden patterns within this research field, bearing substantial implications for urban planning and design. Of particular note, the study revealed significant discrepancies in the distribution centroids between commercial buildings and residential or public buildings. This result illuminates the spatial organization characteristics of urban architectural functions, serving as a valuable reference for urban planning and development. Moreover, it uncovers the advantages and disadvantages of different data sources and techniques in interpreting urban spatial perception, paving the way for a more comprehensive understanding of the subject. These findings underscore the importance of integrating both objective mapping and subjective perspectives in urban architectural functionality classification.

Variations in groundwater levels that are noticed in different parts of the world are typically the primary focus of research carried out in hydrology. The fluctuating levels of groundwater can be ascribed to several different factors, some of which include an increase in the demand for water, inappropriate irrigation practices, improper management of soil, and unregulated extraction from aquifers. It is necessary to effectively manage groundwater resources to have a trustworthy method of measuring and forecasting groundwater levels. The dynamics of groundwater are inherently uneven and difficult to understand. As a result, applying methods driven by data could potentially yield significant gains in hydrology. In this study, two data-driven models were utilized to estimate groundwater levels at a total of 4 monitoring wells located in Colorado state, USA. These models included ARIMA and ANN. The comparative analysis of the algorithms made use of a data set that had one month's worth of information from each of the years 1980 to 2019. The models were put through their paces, and the results of those tests were statistically and visually assessed. To evaluate the relative accuracy and precision of the models, the mean absolute error (MAE), mean square error (MSE), and root-mean-square error (RMSE) were used. When compared to ARIMA, the analysis demonstrates that ANN can produce the most accurate forecasts of groundwater levels in Colorado state USA.

This research paper explores the transformative potential of immersive media, specifically virtual reality (VR), in enhancing empathy among users. Empathy is vital in fostering understanding, compassion, and social cohesion. Immersive media, with its ability to transport individuals into simulated environments and perspectives, offers unique opportunities to bridge the empathy gap. This paper examines how VR can boost empathy, including perspective-taking, emotional connection, experiential learning, breaking down barriers, and empathy-building simulations. It discusses existing studies and empirical evidence supporting the effectiveness of VR in promoting empathy. The paper acknowledges the ethical considerations and challenges associated with using VR for empathy enhancement, such as avoiding stereotype reinforcement and ensuring inclusive design. By highlighting the potential of immersive media in cultivating empathy, this research paper contributes to the growing field of empathy research and provides insights for the development and application of VR experiences aimed at fostering empathy and understanding in diverse contexts.

Spodoptera frugiperda is a relatively new invasive polyphagous insect pest in Indonesia. So far, S. frugiperda infestation has only been reported in corn, however in other countries S. frugiperda has been known to attack many commercial crops. To date, information on biological parameters of S. frugiperda is limited in Indonesian ecologies. Since host plants are a critical factor for insect life-history and has the potential to be used for pest control strategies, it is important to study the biology and survival of S. frugiperda on different host plants. This research was aimed to study the survival, life cycle, and fecundity of S. frugiperda on different host plants and how it affects pest management. The study was conducted by rearing S. frugiperda on 14 common cultivated host plant species in Indonesia. Survival rate, development time, fecundity, and potential attack rate of S. frugiperda on various tested host plants were analyzed in this study. The findings re-vealed that corn was the main host for S. frugiperda. The ability of S. frugiperda to survive on pa-paya, water spinach, banana, spinach, cucumber, and coco grass indicates that these plants are potential alternate host for S. frugiperda. Long beans, bok choy, choy sum, and beans might be in-dicated as a shelter for S. frugiperda. Meanwhile, inappropriate hosts for S. frugiperda include cabbage, broccoli, and cauliflower due to their low survival rate on these plants. This research implies that these plants have the potential to be used as a hedge, trap, or bunker plant in S. frugi-perda management strategies. However, to prevent a detrimental damage, control methods are needed in integrated manner, including monitoring pest populations, environmental engineering, and conservation of natural enemies.

This paper proposes a new battery balancing control strategy based on state of charge (SOC) for addressing the problem of cell-to-cell differences in lithium-ion battery systems. The strategy utilizes a reconfigurable converter system to transfer energy from high-SOC battery modules to low-SOC battery modules and allows balancing the battery modules while they are powering the load. A MATLAB/Simulink simulation model with five batteries was built to validate the effectiveness of the proposed balancing strategy under unloaded and loaded conditions. The simulation results demonstrate that the proposed strategy achieves more efficient and accurate battery module balancing compared to the previous balancing modes, thus increasing the overall lifespan and safety of the battery pack.

2,7-bis(pyridin-4-ylethynyl)-9H-carbazole (1) was synthesized by reacting 4-ethynylpyridine hydrochloride with 2,7-dibromo-9H-carbazole. The full characterization of compound 1 is presented, and the crystal structure of its monohydrate co-crystal was determined by single-crystal XRD analysis.

The health of urban citizens is defined by how their living environments are planned, built, and operated. These complex relations between health and the characteristics of built environments require system-orientated thinking and transdisciplinary interventions, yet have mainly been addressed using conventionally narrow sector-based approaches. This paper investigates the opportunities and challenges of the Vietnamese Green Building Movement (GBM) based on a transdisciplinary approach, with attention to additional health benefits of green buildings that are currently under-researched, while highlighting building users’ perspectives. Focusing on the perspectives of high-rise building residents, the paper examines transdisciplinary insights collected from six thematic webinars, expert interviews, and, in particular, from a household survey conducted in Ho Chi Minh City, Vietnam. Among other findings on opportunities and challenges for the Vietnamese GBM, the paper points out a challenging mismatch between the high importance homebuyers place on green building health benefits, and the focus of GBM stakeholders on GB energy-saving benefits- which are not necessarily homebuyers’ most pressing concerns. With this evidence-based inquiry, the paper concludes that improved health and well-being should be considered co-benefits of green buildings, along with energy efficiency. Importantly, this paper also brings attention to the necessity of a systemic and transdisciplinary approach in both academic and practical efforts toward the implementation of SDG3- to “ensure healthy lives and promote wellbeing for all ages”- and SDG 11- “to make cities and human settlements inclusive, safe, resilient and sustainable”.

As an emerging network paradigm, Space-Air-Ground integrated networks (SAGIN) has attracted the attentions from academia and industry. That is because SAGIN can implement seamless global coverage and connections among electronic devices in space, air, and ground spaces. Additionally, the shortages of computing and storage resources in mobile devices greatly affect the quality of experiences for intelligent applications. Hence, we devise to integrate SAGIN as an abundant resource pool into mobile edge computing environments (MEC). To facilitate efficient processing, we need to solve the optimal task offloading decisions. Different from the existing MEC task offloading solutions, we have to face some new challenges, such as the fluctuation of processing capability for an edge computing node, the uncertainty of the transmission latency caused by the heterogeneous network protocols, the uncertain amount of uploaded tasks during a period, and so on. In this paper, we firstly describe a task offloading decision problem in new challenge environments. But, we cannot use the standard robust optimization and stochastic optimization methods to obtain the optimal result under the uncertain network environments. In this paper, we propose the condition value at risk-aware distributionally robust optimization algorithm, named as CVAR-DRO, to solve the task offloading decision problem. The proposed CVAR-DRO method combines the distributionally robust optimization and the condition value at risk model for solving the optimal result. And then, We have evaluated our approach in simulation SAGIN environments with the confidence interval, the number of mobile task-offloading and the various parameters. We compare our proposed CVAR-DRO algorithm with the state-of-the-art algorithms, such as the standard robust optimization algorithm, the stochastic optimization algorithm, the DRO algorithm, and the brute algorithm. The experimental results show that CVAR-DRO can get a sub-optimal mobile task-offloading decision. Overall, CVAR-DRO is more robust than others to the new challenges mentioned above in SAGIN.

Building Information Modelling (BIM) has been more popular in the construction industry as a consequence of the many advantages it offers, such as increased productivity, improved project outcomes, and reduced expenses. However, there are many obstacles that must be overcome before BIM can be widely used. This research uses a poll of construction industry experts to investigate the challenges associated with using BIM in projects. Cost of implementation, inadequate standards and procedures, and a lack of knowledge with BIM were some of the hurdles that were measured in the study. Statistical techniques were used to examine the data, and the findings indicate that the high cost of implementation and the absence of sufficient standards and procedures are the two main obstacles to the widespread adoption of BIM. Problems with supply chain management and a lack of experience with BIM are also mentioned as obstacles. The report also suggests solutions, such as a more focused teaching effort on BIM-related issues and the creation of a specialised BIM curriculum. Professionals in the construction industry may utilise the study’s results to their advantage by expanding their knowledge of the obstacles standing in the way of widespread adoption of BIM.

The heritage of ancient buildings is an important part of the world's history and culture, which has an extremely rich historical-cultural value and artistic research value. Beijing has a large number of palace ancient buildings, and because of the age of their construction, many of them have problems of varying degrees of peeling and mold on the inner surfaces of the envelope. To solve the problems of the damp and moldy interior of palace buildings, a mathematical model of indoor heat and moisture transfer was established based on a wooden palace ancient building in Beijing. Through the indoor mold distribution validation model, the effects of outdoor humidity, soil moisture, wall humidity, and other factors on the indoor heat and moisture transfer of ancient buildings were simulated and analyzed by using the control variables method. The results showed that the molds were distributed at the indoor corners and floors, and the simulation of indoor humidity match the measured humidity. Thus, the simulation results were consistent with the actual situation. The variable trend of the relative humidity of the indoor environment with the outdoor humidity is inconsistent from plane to plane, i.e. it increases or remains constant with the increase of the outdoor humidity. The indoor ambient relative humidity increased with increasing the wall humidity. And the indoor average temperature is 23.3 ℃ and indoor relative humidity ranged between 90.9 % to 92.44 %. Soil moisture and wall humidity were the main factors affecting the indoor environmental relative humidity.

Advancements in Parametric Design, Generative Design, and automation in Building Information Modelling (BIM) have opened new opportunities for architects and engineers working on complex buildings, such as offices. These developments allow designers to enhance their designs, increase project efficiency, improve performance, and reduce project time and costs. To address conflicting objectives that arise during the design process, genetic algorithms with multi-objective optimization (MOO) have been employed in architectural design. The GENIUS project aims to optimize building shape, apertures, and shading systems in the concept and design stages, with a focus on energy and daylight performance. The project integrates BIM and visual programming tools with Artificial Intelligence techniques like Genetic Algorithms and RBFOpt model-based optimization. Optimization algorithms are used to identify the best solutions that meet all design objectives, helping architects optimize their designs and achieve desired outcomes. The workflow was tested on a case study of a large office building, with MOO focused on maximizing daylight performance using Spatial Daylight Autonomy metric and minimizing energy consumption using Energy Use Intensity metric. The project provides architects with a method to improve their designs using Algorithm Aided Design tools, which help identify the best solutions for complex design problems.

Considering the current energy environment, both efficient and environmentally friendly solutions have to be developed for building construction. Bio-based building materials offer new perspectives through their insulating and natural humidity regulation capacities. Nevertheless, these materials are as complex as they are promising and grey areas still remain regarding their behavior. Their water sorption and desorption curves recorded in experimental work demonstrate a hysteresis phenomenon and, although plausible hypotheses have been formulated in the literature, there is currently no consensus on its causes. Furthermore, it is important to emphasize that no reference considers the hydrophilic nature of the resource. Yet this is a specificity of raw material coming from the plant world. In this context, this paper explores the microstructure and chemical composition of plant aggregates to propose a new explanation for the hysteresis. It is based on recent work demonstrating the existence of differentiated hydrogen bonds between the water sorption and desorption phase in cellulose. Obviously, hysteresis also has an origin at the molecular scale. Lastly, the hypothesis put forward here is supported by the swelling of bio-based materials that has been observed at high relative humidity and this study aims to identify a link between the mechanical (swelling/shrinking) of bio-based materials and their hygroscopic behavior. This leads to a better understanding of the hydro-mechanical coupling of these materials.

Existing studies provide evidence that buildings and the construction sector are the largest consumers of natural resources and carry the greatest responsibility for greenhouse gas emissions. In order to reverse this situation, future challenges involve utilising the least resources possible. To this end, building refurbishment becomes a crucial strategy given its potential to improve operational energy efficiency and to extend the life span of existing building stock, thereby reducing the environmental impact while also providing social and economic benefits to our cities. Life Cycle Sustainability Assessment (LCSA) has become one of the scientific community’s most widely recognised methodologies for the evaluation of the social, economic, and environmental dimensions (Triple Bottom Line), since it assesses sustainability using quantitative metrics. However, the implementation of this methodology to support the refurbishment process at the project stage in building design tools, such as BIM, remains scarce. One of the main obstacles lies in the difficulties of accessing the building information, given that the system boundaries only cover new materials and products. Hence, this study proposes a BIM plug-in development to support the multi-dimensional building material selection in the early design steps based on the LCSA of a building during the refurbishment stage and validates its application in a case study. The results show the viability of using this tool during the early design stages and demonstrate the consistency of the results to evaluate various material and product alternatives for the refurbishment of the envelope system of a multi-family residential building. This study contributes towards the integration of decision-making by providing real-time assessment of the building envelope.

In the traditional power system, customers respond to their primary electricity consumption pattern based on price or incentive to take additional advantages. By developing energy hubs (EHs) where electricity, heat, natural gas and other forms of energy are coupled together, all types of energy customers even the inelastic loads can participate in demand response (DR) program. This novel vision has led to the concept of "integrated demand response (IDR)". IDR programs (IDRPs) in EHs involve coordinating multiple DR activities across different energy systems, such as buildings, industrial complexes, and transportation networks. The main purpose of IDR is that multi-energy users can respond not only by shifting or reducing energy consumption from the demand side, but also by changing the type of energy consumed, in response to the dispatching center. The integration of IDRPs in EHs can help to reduce energy costs, improve grid stability, and increase the penetration of renewable energy sources (RES) in the power system. Moreover, by synchronizing DR activities across different energy systems, IDRPs can provide additional benefits, such as improved energy efficiency, reduced greenhouse gas emissions, and increased resilience to power outages and other disruptions. In this paper, we provide a review, assessment, and classification of fundamental principles, modeling techniques and optimization methods for IDR programs in EHs.

8-Hydroxydeoxyguanosine (8-OHdG) was the most widely used oxidative stress biomarker of the free radical-induced oxidative damage product of DNA, which may allow a premature assessment of various diseases. This paper designed a label-free, portable biosensor device to direct detect 8-OHdG by plasma coupled electrochemistry on transparent and conductive indium tin oxide (ITO) electrode. We reported a flexible printed ITO electrode made from particle-free silver and carbon inks. After inkjet printing, the working electrode was sequentially assembled by gold nanotriangles (AuNTAs) and platinum nanoparticles (PtNPs). This nanomaterial-modified portable biosensor showed excellent electrochemical performance for 8-OHdG detection from 10 μg/mL to 100 μg/mL by our self-developed constant voltage source integrated circuit system. This work demonstrated a portable biosensor for simultaneously integrating nanostructure, electroconductivity, and biocompatibility to construct advanced biosensors for oxidative damage biomarkers. The proposed nanomaterial modified ITO-based electrochemical portable device was a potential biosensor to approach 8-OHdG point-of-care testing (POCT) in various biological fluid samples, such as saliva and urine samples.

The Agile Building Adaptation (AgiBuild) framework is the adoption and adaptation of the large-scale agile framework for building adaptation projects. The agile methodology is proven to drive innovation by focusing on adaptation to change and user centricity. Similarly, the authors envision that the AgiBuild framework can fundamentally change the way that buildings are re-designed, refurbished, and operated. The AgiBuild framework is developed from the need of the building adaptation industry to manage uncertainties, overcome communication barriers, and improve innovation. In this study, a literature review of Agile and its impact on building adaptation projects is undertaken. Based on this systematic literature review, this paper defines the AgiBuilt framework and provides its benefits and barriers to implementation. A key finding of the literature review is that leadership influence, and adequate training form the key foundation for the implementation of the AgiBuild Framework. In defining the AgiBuild framework, the paper describes its components and how its implementation is likely to proceed. The authors propose that by adopting the AgiBuild framework, the industry can transform itself into a highly innovative and user-centred industry to improve productivity and performance of the construction industry..

According to architectural standards, the common proportion of a rectangular-shaped classroom is the shallow proportion, which has a longer external room facade versus the perpendicular internal sides. Even in the Kingdom of Saudi Arabia (KSA), the same proportion is used in school projects. Environmentally, this proportion is logical when considering the role of adequate natural lighting for classroom visual functions, which could be more easily achieved if its longest side is the external one. But, the environmental efficiency of any architectural space cannot be only judged according to a single human comfort achievement, especially with the diverse environmental characteristics of places around the world. This diversity can show a defect in other human comfort achievements or other environmental issues in different ways when achieving a certain function in a unified way. A holistic study should be done for any common architectural shape or proportion to ensure their priority among other options in achieving maximum green architectural principles for a specific location before confirming and using it. The manuscript compares a rectangular classroom of different external/internal wall proportions to search for their preference to be used in Taif city schools in KSA. The compared case studies have different window variations and similarities to include their effect too. According to the overall green principles assessment, the results showed that the common proportion of classrooms didn’t give the higher green credits, which alerts us that the traditional rectangular classroom proportion is not always optimum for all regions including Taif city in KSA.

Lately Silicon Carbide (SiC) and Galium Nitride (GaN) based high frequency power conversion has gained immense popularity which stems from relatively low switching energy, robustness to high temperature operation, wide-band gap and superior thermal limits. While this aspect inherently results in a high-density power stage design, the design of adjoining passive components, particularly magnetics, needs careful attention. This is especially true if the compatibility of core and winding options and their performance is limited with the use of higher switching frequency. In this regard, this paper presents a brief review of existent research conducted in materials, optimization and integration of magnetics for single and three phase applications, ranging from filters, resonant inductors to isolation transformers. Design knobs pertaining to medium voltage (MV) applications, low-voltage (LV) applications, e-mobility sector such as more electric aircrafts (MEAs) and electric vehicles (EVs) are discussed. Guidelines for magnetics design are summarized for each application with a projected roadmap on future trend for magnetics.