Integrated Modelling Techniques Research Articles

An Integrated Building Information Modeling and Life-Cycle Assessment Approach to Facilitate Design Decisions on Sustainable Building Projects in Canada

In the context of the digital and sustainable transformation of building projects, the integrated approach of Building Information Modeling (BIM) and life-cycle assessment (LCA) has been widely studied. Recent advancements in such integrated modeling processes and techniques have not yet provided reliable and robust decision-making capabilities for designers to intuitively choose between material alternatives. This study develops a new design framework that integrates BIM, LCA, and multi-criteria decision-making (MCDM) algorithms to facilitate sustainable design processes in building projects. A case study using a single-family housing project in the British Columbia province of Canada was implemented to test the designs to demonstrate the effectiveness of the proposed integrated framework, including a three-way comparison of design scenarios—conventional hot-roll steel, recycled steel, and timber. The results indicate a significant performance improvement with the adoption of recycled structural steel materials, surpassing conventional steel designs and demonstrating a similar performance to that of timber designs. The study underscores the importance of informed decision-making in material selection, driven by the quantitative analysis of digital designs and multi-criteria evaluation (e.g., social carbon cost). This integrated framework offers a valuable tool for designers, engineers, and builders to achieve sustainability when designing building projects through the systematic and rapid comparison of environmental performance.

Eco-pesantren modeling for environmentally friendly behavior: new lessons from Indonesia

<em><span lang="EN-US">Pesantren</span></em><span lang="EN-US"> or Islamic boarding school plays a vital and strategic role in improving environmentally sound education. </span><em><span lang="EN-US">Eco-pesantren</span></em><span lang="EN-US"> is a movement that puts a high concern for the environment. This study aimed to analyze </span><em><span lang="EN-US">eco-pesantren</span></em><span lang="EN-US"> modeling techniques in education. It is a case study with a qualitative research method. The research was conducted at Islamic Boarding School Sumber Mental Agama Allah (SPMAA), Turi Lamongan, East Java, Indonesia. Data were collected by observation, interviews, questionnaires, and document studies. This research concluded that modeling techniques can at least be pursued in four main ways: the individual role model of </span><em><span lang="EN-US">pesantren</span></em><span lang="EN-US"> leaders; infrastructure and their use; governance systems; and culture or traditions. Besides, using integrated modeling techniques at both school and </span><em><span lang="EN-US">pesantren</span></em><span lang="EN-US"> culture can increase insight and application of environmentally friendly behavior through a direct observation and habituation of healthy educational practices. Modeling can help students turn abstract ideas of green life into actual implementations. Direct observation of continuous practices equips students with the knowledge required to perform expected behaviors. Research on modeling assists </span><em><span lang="EN-US">eco-pesantren</span></em><span lang="EN-US"> institutions encourage learning and practices about healthy environment. In the global context, it can be a role model for the implementation of environmentally friendly education that promotes environmentally sound learning.</span>

Comparative analysis of nonlinear behavioral models for GaN HEMTs based on machine learning techniques

AbstractA variety of novel behavioral modeling techniques have been reported to accurately capture the nonlinear characteristics of GaN devices. For the purpose of describing GaN HEMT large‐signal behavior, machine learning‐based approaches have been proposed. There is, however, a lack of comparison and analysis of their performance with different machine learning techniques in these studies. An examination of machine learning‐based large‐signal modeling techniques is presented in this article. To develop large‐signal models of GaN HEMT, a range of commonly used modeling techniques such as artificial neural networks (ANN), random sample consistency (RANSAC), support vector regression (SVR), Gaussian process regression (GPR), decision trees (DTs), and genetic algorithm‐assisted ANN (GA‐ANN) are described and employed. Afterwards, integrated modeling techniques such as Bootstrap aggregation (BA), random forests (RF), AdaBoost, and gradient tree boosting (GTB) are reviewed and tested for their capabilities in developing GaN HEMT LSM. The hyperparameters of each built model are modified using the random search optimization (RSO) method, and five‐fold cross‐validation is used during validation. In order to identify optimal algorithms for nonlinear behavioral modeling of GaN devices, the model prediction results are comprehensively analyzed.

Integrated modelling techniques to implication of demographic change and urban expansion dynamics on water demand management of developing city in Lake Hawassa Watershed, Ethiopia

Hawassa is a rapidly developing city in the Lake Hawassa watershed of Ethiopia that is a continuous change in the face of an urban environment. The urban development has been increasing the challenge to maintain urban services and surrounding environmental quality. These exert a new challenge to the growing gap between urban water demand and supply balance. Correlating urban growth and water demand to a rapidly growing population remains imperative to adaptive urban planning and decision-making. This study quantified urban development with demographic change and urban expansion dynamics. The population statistics and satellite imageries of historical years 1991–2021 and projections to the year 2051 were analysed using the exponential increase model and geospatial techniques. Multiple empirical modelling approaches were employed to link urban water demand with the explanatory variable. The study findings revealed the projected urban population reach more than one million and 79.2% of urbanization by 2051. With the current trend of 8.9% built-up growth rate, urban area will cover 73.6 km2 (45.9%) for the predicted period. The demographic variables and the sprawl of urban expansion jointly influence the water demand with statistically significant (f = 0.000, at α = 0.05) association. An increase in urban water use efficiency also reduces the water demand by increasing the availability of water supplies. Thus, the proposed model can be applied to reset the emerging relationship between the explanatory variables and water demand management. A detailed consideration of the spatially explicit effect on access to and optimization of the urban water supply system is vital to a local-specific solution. Integrating urban land planning with water demand management, therefore, has the potential to minimize the need to construct additional water supply infrastructure and cheer a sustainable urban environment.

Application of telemetry and stable isotope analyses to inform the resource ecology and management of a marine fish

Abstract Animal movement and resource use are essential considerations for effective environmental management, but they are challenging to quantify in expansive natural ecosystems such as oceans. We used a novel combination of fish tracking with expansive acoustic telemetry networks, stable isotope analysis and integrated modelling techniques to characterize the spatial and trophic ecology of a marine fish species, permit Trachinotus falcatus, and to address specific resource management needs in the Florida Keys. Tracking‐based movement patterns indicated that permit remained primarily within the designated fisheries management unit (92% of individuals), but they moved frequently among distinct habitat types and fisheries. Movement metrics from 109 individuals were integrated into Bayesian isotope mixing models, revealing variable reliance on seagrass‐ versus offshore/pelagic‐based energy channels amongst individuals. Variance was driven mainly by fish habitat use and home range size (km2). A telemetry‐based regional isoscape, informed by individual‐level estimates of resource use (% seagrass reliance; median = 70%, 29%–100% range), illustrated connectivity among habitats and fisheries. Specifically, seagrass flats were highly connected with the Florida reef tract, with frequent movements between these habitat types and a high reliance on seagrass‐based prey. There was a distinction between these fish and those occupying artificial reefs, with the latter showing high use of pelagic/offshore (i.e. planktonic) energy channels. Synthesis and applications. This study used a novel combination of telemetry, stable isotope analysis and integrated modelling techniques to identify two distinct ecotypes of a nearshore fish species, permit, in the Florida Keys. Of the two ecotypes, nearshore Florida Keys permit support multiple valuable fisheries; for these fish management should prioritize conservation of seagrass flats as a key permit food source, as well as fisheries protection measures at spawning sites on the Florida reef tract. This study highlights the capacity for integrated telemetry‐isotope models to provide key insights into animal ecology that has direct implications for applied environmental management.

The costs of increasing precision for ecosystem services valuation studies

• Precision as judged by study authors increases as more time and money is spent on valuation studies. • Perceived precision increases with a study’s total cost ((adjusted R 2 = 0.29, p = 0.018) • Perceived precision increases with the number of person years required to complete it (R 2 = 0.31, p = 0.22) • Available resources (expertise, time, money), desired scope, and necessary precision help choose the appropriate ESV method. • Data availability and collection remain the main constraints in conducting ESV studies. Ecosystem services valuation (ESV) is increasingly used to provide the impetus to sustainably manage and restore ecosystems. When undertaking an ESV study, the available resources, desired scope, and necessary precision must be considered before determining the most appropriate approach. A broad range of techniques exist to support valuation studies, requiring a range of financial, time, and personnel resources. We surveyed authors that completed 56 responses around valuation studies regarding their total costs (including personnel costs) and the perceived precision of their results. Results show that the perceived precision of their results is statistically significant and increases with the cost of a study (adjusted R 2 = 0.29, p = 0.018) and the number of person years required to complete it (R 2 = 0.31, p = 0.22). Understanding the trade-offs between the costs of the study and the precision of the results allows policymakers and practitioners to make more informed decisions about which ESV methods are most cost effective for their needs. For example, basic value transfer techniques require minimal resources to implement but lack precision in the final estimates, while integrated modelling techniques provide dynamic, spatially explicit, and more precise estimates but are significantly more expensive and time consuming to implement. However, these techniques are not mutually exclusive. A quick, inexpensive initial analysis may support and motivate more elaborate and detailed studies.

Spatio-temporal analysis of land use and land cover change: a systematic model inter-comparison driven by integrated modelling techniques

ABSTRACT Currently, land use and land cover change (LULCC) is of utmost concern for global environmental change and sustainability. Among the portfolio of techniques, modelling is considered as the best approach to explore LULC dynamics. We have performed a model inter-comparison exercise (including hybrid and non-hybrid models) using multiple performance metrics to identify the best modelling approach for the subsequent projection of future LULC. The methodology is demonstrated on the Subarnarekha basin of Eastern India by utilizing the LANDSAT imagery of 1989, 1994, 2006, and 2011. Before LULC modelling, the cross-tabulation and trend-surface analyses were performed to identify dominant land transitions in post-classification maps. Temporal mapping results over 1989–2011 exhibited a drastic decrease in the area under dense forest (25.7% to 19.0%), a substantial increase in the area under scrubland (21.0% to 26.1%) and a nominal reduction in the coverage of the agricultural land (51.2% to 49.0%). Four integrated models namely Multilayer perceptron-Markov Model (MLP-MC), Logistic Regression-Markov Model (LR-MC), and two hybrid models, i.e. Multilayer perceptron-Cellular automata-Markov model (MLP-CA-MC) and Logistic Regression-Cellular automata-Markov model (LR-CA-MC) were tested for their suitability for predicting future LULC for the basin. Based on the multiple model validation techniques, the MLP-MC model performed the best. MLP-MC model subsequently used a non-stationary relationship between selected explanatory variables and LULC to predict the future LULC for 2020 and 2030. The MLP-MC model projected that relative to the level of 2011, agricultural land, dense forest, and barren land may decrease by 8.3, 28.2 and 23.5%, respectively, and scrubland, built-up area, and water bodies may increase by 22.5, 87.3 and 13.3%, respectively, by 2030. Our findings contradict the prevalent view regarding the nationwide intensification of agriculture over the Indian subcontinent but are consistent with the national decreasing trend in the dense forest. The study provides a transferable methodology for the systematic comparison of LULC models (including hybrid and non-hybrid) against multiple performance metrics. The outcomes of the study may help land-use planners, environmentalist, and policymakers in framing better policies and management .recommendations.

On the Structural Basis of Group 1 Influenza Fusion Inhibition by Arbidol

Influenza virus infection continues to be a major healthcare issue and the combination of the strain-specificity of vaccines with the increased circulation of therapeutic resistant strains drives the need for new approaches for the prevention and treatment of infection. Arbidol is a broad-spectrum antiviral with demonstrated activity against both group 1 and 2 influenza hemagglutinin (HA) subtypes. While the Arbidol binding site has been determined for group 2 HAs, it remains unidentified for group 1 HAs. Further, based on differences between group 1 and group 2 HAs, it is unknown whether or not Arbidol binds in a group-specific manner. Here, integrative modeling techniques combining cryo-electron tomography with x-ray crystallography and homology modeling enabled the construction of an all-atom model of the 2009 H1N1 influenza viral coat. Using the petascale supercomputer Blue Waters, we have performed explicitly solvated, all-atom molecular dynamics simulations of this model, which contains over 160 million atoms and spans ~120 nm in diameter. From the subcellular scale simulations, individual HA trajectories have been extracted and analyzed with the construction of a Markov state model. Doing so allows us to investigate the structural dynamics and conformational transitions of the HA glycoprotein in the context of the crowded viral surface. From our Markov state model, we present the first evidence of a druggable pocket in a group 1 HA that is able to accommodate Arbidol. This druggable site is located in an analogous position to the known group 2 Arbidol binding site, suggesting that the binding of Arbidol to influenza HA is not group specific. The structural insights obtained here provide a structural basis for the mechanism of action for this drug in a group 1 HA, and thus will facilitate the development of the next generation of influenza therapeutics.

Status of urban hydrogeology research with emphasis on India

Urban areas have witnessed an inexorable expansion in population density, urban sprawl, industrialization and agricultural activities in the past few decades. Withdrawal of groundwater to meet water demand has resulted in over-drafting of aquifers and, commonly, lowered water tables in many urban centres of India, like Delhi, Lucknow, Patna, Kolkata and others. Overdraft has also deteriorated the chemical and biogeochemical quality of surface water and groundwater. This paper highlights some of the research approaches, namely hydrogeochemical investigation, groundwater modeling, and use of geographic information systems and remote sensing, used worldwide to resolve issues specific to urban groundwater. The paper also highlights approaches that are practiced internationally (combined hydrogeologic and multi-isotopic studies, integrated modeling techniques, etc.) but still need to be developed on a large scale in India. A detailed overview of the literature indicates the need for a more holistic approach incorporating various types of conceptual and management models to strengthen the research level in India and elsewhere. For instance, a computational tool that can incorporate different models, such as for urban water and contaminant balance and pipeline leakage, should be developed to generate predefined scenarios of potential groundwater contamination and help in the socio-economic analysis of different scenarios. In hydrogeochemical approaches, multi-isotope ratios should be coupled with hydrogeologic approaches for better understanding of water quality problems.

Auto-regulation of Rab5 GEF activity in Rabex5 by allosteric structural changes, catalytic core dynamics and ubiquitin binding.

Intracellular trafficking depends on the function of Rab GTPases, whose activation is regulated by guanine exchange factors (GEFs). The Rab5 GEF, Rabex5, was previously proposed to be auto-inhibited by its C-terminus. Here, we studied full-length Rabex5 and Rabaptin5 proteins as well as domain deletion Rabex5 mutants using hydrogen deuterium exchange mass spectrometry. We generated a structural model of Rabex5, using chemical cross-linking mass spectrometry and integrative modeling techniques. By correlating structural changes with nucleotide exchange activity for each construct, we uncovered new auto-regulatory roles for the ubiquitin binding domains and the Linker connecting those domains to the catalytic core of Rabex5. We further provide evidence that enhanced dynamics in the catalytic core are linked to catalysis. Our results suggest a more complex auto-regulation mechanism than previously thought and imply that ubiquitin binding serves not only to position Rabex5 but to also control its Rab5 GEF activity through allosteric structural alterations.

Influenza Viral Envelope Simulation Reveals Novel Druggable Pockets on Surface Glycoproteins

Influenza virus infection continues to be a major healthcare issue, with 3-5 million cases of severe disease reported and 300,000-500,000 deaths worldwide each year. Variation in the sequences and structures of the two major surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA), from strain to strain complicate prophylactic and therapeutic approaches. Integrative modeling techniques combining cryo-electron tomography with x-ray crystallography, homology modeling, and protein-protein docking have led to the construction of a whole-virion model of influenza. Using the petascale computing machine Blue Waters, we have performed molecular dynamics (MD) simulations of this virion model. Principal component analysis reveals that simulation of the complete virion allows exploration of greater glycoprotein conformational space as compared to single glycoprotein simulations. Further, Markov state models constructed from the trajectories of the glycoproteins reveal novel druggable pockets in both HA and NA that can be targeted for the development of novel treatments for influenza virus infection. The identification of potentially druggable pockets previously unseen in simulations of individual glycoproteins demonstrates the utility of modeling in the sub-cellular scale and beyond to inform drug discovery.

Integrative modeling techniques applied to resolving ambiguous sequence assignment in DNAPKcs

Integrative modeling techniques applied to resolving ambiguous sequence assignment in DNAPKcs

Who is the Expert? Integrated Urban Modeling and the Reconfiguration of Expertise

ABSTRACTMuch has been spoken and written about the rationalization and optimization of services and amenities in urban territories. In this context, there is increasing use of numerical modeling techniques addressing the design, selection and/or calibration of policy instruments. The question of the relations between appraisal tools and policymaking has been widely studied. However, few studies have specifically focused on the role of modeling in policymaking processes. Drawing on two case studies, this paper suggests a change in the nature of multi-expertise: neither conflicting nor cross-sectoral, we observed in both cases an interwoven configuration with a network of experts making use of integrated models. We call this configuration distributed expertise, arguing that it is a novel configuration and that its emergence is closely linked to the development of integrated modeling techniques. Other authors have discussed the idea that the growing need for new appraisal tools is linked with the proliferation of wicked policy problems. From our case studies we would conclude that the emergence of integrated modeling is not a response to complex problems but to complex systems of actors who need to reach a consensus on actions.

Geological and geophysical integrated interpretation and modelling techniques

Exploration is becoming harder, at depth or under cover and decisions need to be made in model rather than data space; supported by multiple data sets. Geophysics plays an ever increasing role and integration of information from various geophysical data sets in tight collaboration with geological control is required to maximise the return from the individual data sets. In terms of integrating geological and geophysical data, the essential goal is to interpret the available geophysical data in terms of geological domains. The process requires a common sense approach to interpretation that is flexible, adaptive and objective driven. It is not an exact formula or procedure; particularly when multiple geophysical surveys are involved. Understanding the relationships between geology, geophysical responses and rock properties is the key to develop a geological basis for your integrated interpretation. Following this, rapid 3D geological modelling and geologically based forward modelling and inversion are essential for model validation and quantitative integration of data. An integrated interpretation is not necessarily the simplest approach, but does provide answers to geoscientific questions that are stronger than individual elements interpreted on their own. This paper presents a review of the mechanics involved in integrated interpretation and demonstrates the results with selected case study examples.

Static and Dynamic Aspects of Application Domains: An Inductively Defined Modeling Technique That Allows Decomposition

Modeling is one of the most important parts of requirements engineering. Most modeling techniques focus primarily on their pragmatics and pay less attention to their syntax and semantics. Different modeling techniques describe different aspects, for example, Object-Role Modeling (ORM) describes underlying concepts and their relations while System Dynamics (SD) focuses on the dynamic behavior of relevant objects in the underlying application domain. In this paper we provide an inductive definition for a generic modeling technique. Not only do we describe the underlying data structure, we also show how states can be introduced for relevant concepts and how their life cycles can be modeled in terms of System Dynamics. We also show how decomposition can be applied to master complex application domains. As a result we get an integrated modeling technique covering both static and dynamic aspects of application domains. The inductive definition of this integrated modeling technique will facilitate the implementation of supporting tools for practitioners.

Developing Robust Predictive Models for Head and Neck Cancer across Microarray and RNA-seq Data.

Increased understanding of the transcriptomic patterns underlying head and neck squamous cell carcinoma (HNSCC) can facilitate earlier diagnosis and better treatment outcomes. Integrating knowledge from multiple studies is necessary to identify fundamental, consistent gene expression signatures that distinguish HNSCC patient samples from disease-free samples, and particularly for detecting HNSCC at an early pathological stage. This study utilizes feature integration and heterogeneous ensemble modeling techniques to develop robust models for predicting HNSCC disease status in both microarray and RNAseq datasets. Several alternative models demonstrated good performance, with MCC and AUC values exceeding 0.8. These models were also applied to discriminate between early pathological stage HNSCC and normal RNA-seq samples, showing encouraging results. The predictive modeling workflow was integrated into a software tool with a graphical user interface. This tool enables HNSCC researchers to harness frequently observed transcriptomic features and ensembles of previously developed models when investigating new HNSCC gene expression datasets.

Cloud to coast: integrated assessment of environmental exposure, health impacts and risk perceptions of faecal organisms in coastal waters

ABSTRACTThe proper recognition and calculation of polluted sources and the fate and transport of faecal organisms in catchments, river networks and coastal waters are very important to the assessment of environmental exposure, health impacts and risk perceptions of faecal indicator organisms (FIO) in coastal waters. The paper reviews the integrated modelling techniques for faecal processes from cloud to coast, including sediment and faecal bacteria interactions, and then presents a theoretical and case study in the numerical modelling for FIO levels in the river Ribble and Fylde Coast using the two-dimensional or three-dimensional environmental fluid dynamics code and the 1D Flow And Solute Transport in Estuaries and Rivers models, respectively. The related key parameters in the linked model are illustrated and analysed, together with validation of the hydrodynamic processes and the faecal bacteria concentration levels being undertaken using measured related data acquired in 1999. Using the model results, a quantitative microbial risk assessment is undertaken, where a moderate dose for swimming in faecal coliform-laden flows is accepted, as given by the European (EU) water quality standard requirements. The results show that some local regions of relatively high concentration exist near the outfalls and these values are not compliant with the mandatory and tighter microbial standards in the UK, as governed by the new EU Water Framework Directive. Finally, some new research and key challenges for the future are discussed in the paper.

Determination of Groundwater Level Based on Rainfall Distribution: Using Integrated Modeling Techniques in Terengganu, Malaysia

Development and effective utilization of groundwater resources is essential especially in semi-arid region and even in a region with abundant rainfall such as the study area for activities such as water supply and irrigation. The present study aims to analyze statistically the groundwater level data and rainfall data of 13 years (2000-2012) collected from the Department of Minerals and Geosciences Terengganu and Department of Irrigation and Drainage Terengganu for the seven (7) stations: Besut, Dungun Jerengau, Kemaman, Bukit, PakaLuit, Cherul at Ho, and Berang Menerong of Terengganu Malaysia. The sum of least square method was adapted to analyses the relationship of groundwater level variability with the rainfall distribution. The analysis indicated that the rainfall distribution has an influence on groundwater level in the study area due to positive relationship indicated by regression analysis. Although in some of the stations the influence is not much significant, that is the groundwater levels depends on runoff and other factors rather than rainfall. Such stations are Site 4930401 SG. Berang at Menerang Terengganu shows 14.7%, Site 4232401 SG. Kemaman at Jam. Air Puteh, Terengganu shows 27.2%, and Site 4732461 SG. Paka at KG.Luit, Terengganu shows 35.2%. The station that shows great influence of rainfall in determining the groundwater level is Site 5229436 SG. Nerus at KG. Bukit, Terengganu which has 58.5%, while the remaining stations are moderate.

Systems Electrochemistry

Beyond the Cartesian framework, emergent processes in many chemical, physical, and biological systems exemplify the maxim ‘the whole is more than the sum of its parts’. An electrochemical reaction provides a prototype example of a complex system where interactions of chemical reactions and physical processes (mass transfer, electrostatics) produce non-trivial, emergent temporal and spatial dependences of reaction rates. The integrative experimental and modeling techniques are the common denominators in Systems Electrochemistry: the main objective is to advance the understanding of emergent properties of electrochemical systems in which many variables are handled simultaneously. A wide range of, typically far-from-equilibrium, systems are considered in electrocatalysis, corrosion, bioelectrochemistry, electrodeposition, batteries, fuel cells, and semiconductor systems. Concrete examples include multistability, periodic and chaotic oscillations, and pattern formation in electrochemical reactions, whole-cell bioelectrochemistry, stability of single and cascaded fuel cells, reaction dynamics coupled with mass transfer, and stochastic corrosion phenomena. System Electrochemistry encompasses thus many electrochemical systems in a transdisciplinary agenda that aims to bring together experts from various fields who use mathematical and experimental approaches for the characterization of dynamical responses in temporal and spatial domains. The adoption of Systems approaches in various fields will expand considerably the understanding of complex electrochemical processes. In this introductory address of the Systems Electrochemistry symposium, we discuss some of these aspects, illustrate examples, and suggest future directions.

The application of componentised modelling techniques to catastrophe model generation

In this paper we show that integrated environmental modelling (IEM) techniques can be used to generate a catastrophe model for groundwater flooding. Catastrophe models are probabilistic models based upon sets of events representing the hazard and weights their likelihood with the impact of such an event happening which is then used to estimate future financial losses. These probabilistic loss estimates often underpin re-insurance transactions. Modelled loss estimates can vary significantly, because of the assumptions used within the models. A rudimentary insurance-style catastrophe model for groundwater flooding has been created by linking seven individual components together. Each component is linked to the next using an open modelling framework (i.e. an implementation of OpenMI). Finally, we discuss how a flexible model integration methodology, such as described in this paper, facilitates a better understanding of the assumptions used within the catastrophe model by enabling the interchange of model components created using different, yet appropriate, assumptions.