Modeling Platform Research Articles

A review of resistance–capacitance thermal network model in urban building energy simulations

With the increasing population and urbanization promotion, energy consumption and carbon emissions have increased, and concern for inefficient energy use and deteriorating urban environments is growing. The prediction of building energy consumption and environmental evaluation, especially at large scales, are considered to be a major challenge confronting the research community. An outstanding strategy for mitigating energy consumption and carbon emissions resides in the field of energy modeling. As a simplified building energy modeling model, resistance–capacitance (RC) network model has the applications in fast predicting building energy consumption. Notably, in recent years, there has been an evident absence of thorough review endeavors related to RC model for urban building energy loads and climate. This review systematically explores the application of low-order models and reduction methods for urban or regional energy simulation starting from the typical RC model for building. In summation, the challenges associated with employing this model for urban building energy loads and climate can be succinctly summarized as follows: the absence of a unified platform for RC modeling; insufficient readily applicable urban datasets; the need for modeling tools that facilitate cross-platform analyses in conjunction with existing Geographic Information Systems (GIS) and urban thermal environment simulation research platforms, and the essential requirement for seamless integration with other complementary modules.

A novel biomechanical model of the mouse forelimb predicts muscle activity in optimal control simulations of reaching movements.

Mice are key model organisms in genetics, neuroscience and motor systems physiology. Fine motor control tasks performed by mice have become widely used in assaying neural and biophysical motor system mechanisms, including lever or joystick manipulation, and reach-to-grasp tasks (Becker et al., 2019; Bollu et al., 2019; Conner at al., 2021). Although fine motor tasks provide useful insights into behaviors which require complex multi-joint motor control, there is no previously developed physiological biomechanical model of the adult mouse forelimb available for estimating kinematics (including joint angles, joint velocities, fiber lengths and fiber velocities) nor muscle activity or kinetics (including forces and moments) during these behaviors. Here we have developed a musculoskeletal model based on high-resolution imaging and reconstruction of the mouse forelimb that includes muscles spanning the neck, trunk, shoulder, and limbs using anatomical data. Physics-based optimal control simulations of the forelimb model were used to estimate in vivo muscle activity present when constrained to the tracked kinematics during mouse reaching movements. The activity of a subset of muscles was recorded via electromyography and used as the ground truth to assess the accuracy of the muscle patterning in simulation. We found that the synthesized muscle patterning in the forelimb model had a strong resemblance to empirical muscle patterning, suggesting that our model has utility in providing a realistic set of estimated muscle excitations over time when provided with a kinematic template. The strength of the resemblance between empirical muscle activity and optimal control predictions increases as mice performance improves throughout learning of the reaching task. Our computational tools are available as open-source in the OpenSim physics and modeling platform (Seth et al., 2018). Our model can enhance research into limb control across broad research topics and can inform analyses of motor learning, muscle synergies, neural patterning, and behavioral research that would otherwise be inaccessible.

Real-time electro-mechanical profiling of dynamically beating human cardiac organoids by coupling resistive skins with microelectrode arrays

Cardiac organoids differentiated from induced pluripotent stem cells are emerging as a promising platform for pre-clinical drug screening, assessing cardiotoxicity, and disease modelling. However, it is challenging to simultaneously measure mechanical contractile forces and electrophysiological signals of cardiac organoids in real-time and in-situ with the existing methods. Here, we present a biting-inspired sensory system based on a resistive skin sensor and a microelectrode array. The bite-like contact can be established with a micromanipulator to precisely position the resistive skin sensor on the top of the cardiac organoid while the 3D microneedle electrode array probes from underneath. Such reliable contact is key to achieving simultaneous electro-mechanical measurements. We demonstrate the use of our system for modelling cardiotoxicity with the anti-cancer drug doxorubicin. The electro-mechanical parameters described here elucidate the acute cardiotoxic effects induced by doxorubicin. This integrated electro-mechanical system enables a suite of new diagnostic options for assessing cardiac organoids and tissues.

Immersive Photorealistic Three-Dimensional Neurosurgical Anatomy of the Cerebral Arteries: A Photogrammetry-Based Anatomic Study.

Neurosurgeons need a profound knowledge of the surgical anatomy of the cerebral arteries to safely treat patients. This is a challenge because of numerous branches, segments, and tortuosity of the main blood vessels that supply the brain. The objective of this study was to create high-quality three-dimensional (3D) anatomic photorealistic models based on dissections of the brain arterial anatomy and to incorporate this data into a virtual reality (VR) environment. Two formaldehyde-fixed heads were used. The vessels were injected with radiopaque material and colored silicone and latex. Before the dissections, the specimens were computed tomography scanned. Stratigraphical anatomic dissection of the neck and brain was performed to present the relevant vascular anatomy. A simplified surface scanning method using a mobile phone-based photogrammetry application was used, and the data were incorporated into a VR 3D modeling software for post-processing and presentation. Fifteen detailed layered photorealistic and two computed tomography angiography-based 3D models were generated. The models allow manipulation in VR environment with sufficient photographic detail to present the structures of interest. Topographical relevant anatomic structures and landmarks were annotated and uploaded for web-viewing and in VR. Despite that the VR application is a dedicated 3D modeling platform, it provided all necessary tools to be suitable for self-VR study and multiplayer scenarios with several participants in one immersive environment. Cerebral vascular anatomy presented with photogrammetry surface scanning method allows sufficient detail to present individual vessel's course and even small perforating arteries in photorealistic 3D models. These features, including VR visualization, provide new teaching prospects. The whole study was done with simplified algorithms and free or open-source software platforms allowing creation of 3D databases especially useful in cases with limited body donor-based dissection training availability.

Leveling up orthodontic education: Game-based learning as the new frontier in orthodontic curriculum

Game-based learning (GBL) is becoming a focal point in contemporary orthodontic dental education. This study examines GBL’s ability to provide immersive experiences simulating real-world orthodontic practice. Leveraging technologies like virtual reality (VR), augmented reality (AR), 3D modeling, and advanced e-learning platforms, GBL enhances active learning, critical thinking, and decision-making skills. While promising, GBL adoption faces challenges like high costs, technical demands, and curriculum integration hurdles. However, ongoing innovations, personalized learning paradigms, and artificial intelligence (AI) are mitigating these. This research highlights GBL’s measurable impact on student engagement, information retention, and translating theory into orthodontic practice. Through GBL’s lens, orthodontic education undergoes a paradigm shift where students construct comprehensive treatment plans for simulated patients, fulfilling modern orthodontic pedagogy’s evolving requirements.

A Develop Strategies Management of Private Tennis in Xi’an City, China

Background and Aims: Developing strategies for managing private tennis programs is critical for maximizing player potential and maintaining a sustainable competitive advantage. It entails tailoring training, facilities, and resources to individual and organizational objectives, resulting in long-term success in the sport. Thus, this paper aims: (1) What are the problems of development strategies management of private tennis clubs? And (2) to develop management strategies for private tennis clubs. Methodology: This research is a survey and interview research. The population used in this research was 21 professionals who are former or current presidents of the Chinese Tennis Association national team coaches and tennis players. Samples mean the l9 experts selected for Purposive selection by determining the characteristics of the sample sampling were as follows: 7 tennis professors and 12 tennis club officers (8 female and 11 male) using Delphi techniques—data analysis using statistics indicator median and interquartile range, and POLC. Results: The tennis club management development platform model effectively develops private tennis clubs in Xi’an City with an average mean of 4.64 on a 5-point Likert scale for agreement. The platform includes: (1) Planning to build a model for private tennis club development strategies management can plan the creation of many forms in the presentation. There are elements of building a platform in the planning that can be used differently. Therefore, it depends on creating a model for managing private tennis club development strategies. (2) Management builds a model for private tennis club development strategies management can be as ranged in many ways and can be organized in many forms, the organization must be ready in all aspects, such as people, places, model tools, and model platform. In modern times, owners are interested in an organization that forms a platform for developing an organization model style. (3) Implementing the practice of creating a model for private tennis club development strategies management can be achieved according to the principles of development strategies management according to the steps of private tennis club development strategies management according to the established guidelines. (4) Controlling the creation of a model for private tennis club development strategies management can control the use of planning at every stage whether it’s an evaluation form measure and control the way to use the model in the right way. Conclusion: The study found that the tennis club management development platform is extremely effective in improving private tennis clubs in Xi'an City, with strong agreement among participants. The platform's success can be attributed to its comprehensive approach, which includes planning, management, implementation, and control. These elements all contribute to the effective development of private tennis club strategies.

Overview of the Research Status of Intelligent Water Conservancy Technology System

A digital twin is a new trend in the development of the current smart water conservancy industry. The main research content of intelligent water conservancy is clarified. This paper first summarizes and combs the relevant system architecture of smart water conservancy, and puts forward a smart water conservancy framework based on digital twins, highlighting the characteristics of virtual and real interaction, and symbiosis of the water conservancy twin platform. Secondly, the status quo of intelligent water conservancy “sky, air, ground and water” integrated monitoring technology, big data and artificial intelligence, model platform technology, knowledge graph and security technology is analyzed. From the perspective of application, the research progress of each technology in water security, water resources and hydraulic engineering is reviewed. Although the construction of smart water conservancy has made remarkable progress, it still faces many challenges such as data governance, technology integration and innovation, and standardization. In view of these challenges, this paper puts forward a series of countermeasures, and looks forward to the future development direction of intelligent water conservancy.

Adaptation of FDMT to include process-based models and consider regional aspects following radionuclide deposition events

Experience from earlier nuclear accidents has clearly shown the need for maintaining and developing appropriate modelling capabilities. Dealing with complex issues such as human exposure following a nuclear accident necessitates the implementation of a set of interconnected models such as FDMT. FDMT is an integrated module within the two main European decision support systems for radiological emergency preparedness, ARGOS and JRODOS, to simulate the transfer of radionuclides along terrestrial food chains and to predict their activity concentrations in foodstuffs. In order to make the module more fit-for-purpose, FDMT has been implemented in a new modelling platform (ECOLEGO) which provides a high degree of flexibility with regard to conducting developmental work. This paper presents improvements in FDMT further through either the incorporation of new models or further elaboration of existing ones, as well as updates in default parameters. Models have also been made more fit-for-purpose through consideration of regional-specific parameters. Specific improvements include modelling developments related to dry deposition, radioactive particle weathering, radiocaesium transfer influenced by soil characteristics and, for a region-specific case, animal uptake. In addition, the paper presents new pathways and parameters (and updated values) to be considered for making FDMT more adapted for Norwegian conditions. Overall, the improvements made in the present work should significantly reduce the uncertainties associated with the outputs of the FDMT models.

Promoting digital twin technology application for process industry: A novel generation modelling platform and its implementations

AbstractOne key concept of Industry 4.0 is the industrial digital twin (DT)—a virtual replica of physical assets, processes, and systems. DTs optimise operations, enhance productivity, and facilitate innovation across various industries, including manufacturing, energy, healthcare, and transportation. This paper presents a multi‐domain and multi‐time scale modelling and simulation platform, featuring built‐in model libraries that represent diverse physical, chemical, and behavioural properties. A comprehensive system modelling approach and a closed‐loop industrial control system based on DTs are developed, showcasing advanced control, optimisation, and system security research capabilities. The architecture and advantages of the novel generation modelling platform are detailed, with specific applications highlighted, underscoring its contributions to the process industry.

P19-74 Platform for transfer models for hazardous compounds in animal feed

P19-74 Platform for transfer models for hazardous compounds in animal feed

Future Agricultural Water Availability in Mediterranean Countries under Climate Change: A Systematic Review

Warming and drying trends in the Mediterranean Basin exacerbate regional water scarcity and threaten agricultural production, putting global food security at risk. This study aimed to review the most significant research on future water availability for the Mediterranean agricultural sector under climate change (CC) scenarios published during 2009–2024. Two searches were performed in the Scopus and Web of Science databases, to which previously identified significant studies from different periods were also added. By applying a methodology duly protocoled in the PRISMA2020-based guideline, a final number of 44 particularly relevant studies was selected for review. A bibliometric analysis has shown that most of the published research was focused on Southwestern European countries (i.e., Spain, Italy, Portugal) and grapevine and olive tree crops. Overall, the reviewed studies state that future Mediterranean water reserves may not meet agricultural water demands, due to reduced reservoir inflows and higher irrigation demands under future CC and socioeconomic scenarios. Regarding adaptation measures to improve water-use management in agriculture, the majority of the reviewed studies indicate that the use of integrated modelling platforms and decision–support systems can significantly contribute to the development and implementation of improved water/land-management practices.

Autonomous Vehicle–Pedestrian Interaction Modeling Platform: A Case Study in Four Major Cities

Autonomous Vehicle–Pedestrian Interaction Modeling Platform: A Case Study in Four Major Cities

P05-31 PBK modelling concepts for a user friendly generic bovine kinetic modelling platform to predict transfer of compounds from feed, veterinary medicines and supplements to food

P05-31 PBK modelling concepts for a user friendly generic bovine kinetic modelling platform to predict transfer of compounds from feed, veterinary medicines and supplements to food

De Novo Design and Characterization of Amphiphilic Peptides with Basic Side Chains for Tailored Interfacial Chemistries.

Lysine-leucine (LK) peptides have been used as model systems and platforms for 2D material design for decades. LK peptides are amphiphilic sequences designed to bind and fold at hydrophobic surfaces through hydrophobic leucine side chains and hydrophilic lysine side chains extending into the aqueous subphase. The hydrophobic periodicity of the sequence dictates the secondary structure at the interface. This robust design makes them ideal candidates for controlling interfacial chemistry. This study presents the de novo design and characterization of two novel peptides: LRα14 and LHα14, which substitute lysine with arginine and histidine, respectively, in the helical LKα14 sequence. This modification is intended to expand the LK peptide platform to a new basic interfacial chemistry. We explore the stability of the new LRα14 and LHα14 designs with respect to changes in pH and salt concentration in bulk solution and at the interface using circular dichroism (UV-CD) and vibrational sum-frequency generation spectroscopy, respectively. Notably, the structural stability of the peptides remains unaffected across a wide range of pH and ionic strength values. At the same time, the variation of side-chain chemistry leads to a wide spectrum of interfacial water structures. By extension of the LK platform to include arginine and histidine, this study broadens the toolbox for designing tailored interfacial chemistries with applications in material and biomedical sciences.

Modelling-Augmented Failure Diagnostics in Planar SiC MOS Devices Using TDDB Measurements

In this study we analyzed the physical mechanisms governing time-dependent dielectric breakdown (TDDB) and we used TDDB physical model of dielectric breakdown, implemented in the defect-centric Ginestra® modeling platform, to deconvolute the intrinsic material properties effects and geometry feature impact on the gate oxide (GOx) and SiC-device breakdown.

The value of simplified models of radionuclide transport for the safety assessment of nuclear waste repositories: A benchmark study

In order to assess sites for a deep geological repository for storing high-level nuclear waste safely in Germany, various numerical models and tools will be in use. For their interaction within one workflow, their reproducibility, and reliability version-controlled open-source solutions and careful documentation of model setups, results and verifications are of special value. However, spatially fully resolved models including all relevant physical and chemical processes are neither computationally feasible for large domains nor is the data typically available to parameterize such models. Thus, simplified models are crucial for the pre-assessment of possible sites to narrow down the list of suitable candidates for which detailed site investigations and fully resolved models will be done at a later stage. Still, the accuracy of these simplified models is of importance as the pre-assessment of suitable sites will be based on them. In this study, we compare the modelling capabilities of TransPyREnd, a one-dimensional transport code based on finite differences, specifically developed for the fast estimation of radionuclide transport by the German federal company for radioactive waste disposal (BGE), with OpenGeoSys, which is a modelling platform based on finite elements in up to three spatial dimensions. Both codes are used in the site selection procedure for the German nuclear waste repository. The comparison of the model results of TransPyREnd and OpenGeoSys is augmented by comparisons with an analytical solution for a homogeneous material. For the purpose of numerical benchmarking, we consider a geological profile located in southern Germany as an example where the hypothetical repository is located in a clay-stone formation. TransPyREnd and OpenGeoSys yield overall similar results. However, both codes use different discretizations which impact is the highest for strongly sorbing compounds, while the difference gets negligible for less sorbing and more diffusive compounds as higher diffusion tends to blur the initial conditions. Overall, the OpenGeoSys model is more exact whereas the TransPyREnd model has considerable faster run times. We found in our example, that significant substance amounts are only leaving the host rock formation, if apparent diffusion is high, for which case both codes give similar results, while relative differences are considerable for strongly sorbing compounds. However, in the latter case no significant substance amount of radionuclides leaves the host-rock formation, thus deeming the differences in the model results minor for the overall safety assessments of sites.

Improving readability and comprehension levels of otolaryngology patient education materials using ChatGPT

ObjectiveA publicly available large language learning model platform may help determine current readability levels of otolaryngology patient education materials, as well as translate these materials to the recommended 6th-grade and 8th-grade reading levels. Study designCross-sectional analysis. SettingOnline using large language learning model, ChatGPT. MethodsThe Patient Education pages of the American Laryngological Association (ALA) and American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) websites were accessed. Materials were input into ChatGPT (OpenAI, San Francisco, CA; version 3.5) and Microsoft Word (Microsoft, Redmond, WA; version 16.74). Programs calculated Flesch Reading Ease (FRE) scores, with higher scores indicating easier readability, and Flesch-Kincaid (FK) grade levels, estimating U.S. grade level required to understand text. ChatGPT was prompted to “translate to a 5th-grade reading level” and provide new scores. Scores were compared for statistical differences, as well as differences between ChatGPT and Word gradings. ResultsPatient education materials were reviewed and 37 ALA and 72 AAO-HNS topics were translated. Overall FRE scores and FK grades demonstrated significant improvements following translation of materials, as scored by ChatGPT (p < 0.001). Word also scored significant improvements in FRE and FK following translation by ChatGPT for AAO-HNS materials overall (p < 0.001) but not for individual topics or for subspecialty-specific categories. Compared with Word, ChatGPT significantly exaggerated the change in FRE grades and FK scores (p < 0.001). ConclusionOtolaryngology patient education materials were found to be written at higher reading levels than recommended. Artificial intelligence may prove to be a useful resource to simplify content to make it more accessible to patients.

Clients’ Perceptions of Authentic Intimate Connection on Erotic Webcam Modeling Sites

ABSTRACT While early uses of technology in the sex industry centered on increasing accessibility to pornography or expanding advertising opportunities for direct service sex workers, the growing prevalence of personalized, platform-based sexual technologies reflects the postindustrial paradigm of sexual labor in which “authentic” emotional and physical connection is increasingly prioritized. In this study, we explored how erotic webcam modeling platforms (e.g. LiveJasmin) exemplify “bounded authenticity” by offering clients an experience of “genuine” intimacy that is nevertheless constrained by both its transactional nature and technological reality. We conducted a web-based survey of LiveJasmin clients (N = 2,047) in 2020. We assessed participants’ perceptions of the authenticity of their emotional bonds with models – and the boundaries that potentially constrain these relationships – via quantitative and qualitative measures. Quantitative results revealed that 65% of participants reported having ever experienced an emotional bond with a model, with over half of participants (51.6%) reporting that they believed the models cared about their lives outside the platform. Providing nuance to these findings, qualitative results illustrated the ways in which participants’ perceptions of the emotional authenticity and boundaries of these relationships varied, with participants reporting a range of experiences that extended from perceived “real” connections to those that feel transactional and hollow, but nevertheless shaped by the platform. Our findings ultimately underscore how camsite clients’ perceptions of these relationships mirror the tension between desiring genuine feelings of emotional intimacy from the models and the market and technological constraints of these experiences.

Implications of landscape changes for ecosystem services and biodiversity: A national assessment in Ecuador

Ecuadorian ecosystems experience high pressure due to anthropogenic activities and climate change. Despite the need of regular monitoring of biodiversity and ecosystem services (BES), attempts to assess the current and future interdependencies of BES and landscape changes are still lacking. This study suggests a spatial assessment of the capacity of ecosystems/land use types to provide BES as status quo and its future development under scenarios of deforestation and climate change. To address data scarcity and improve legitimacy, spatial modeling was combined with participatory approaches. Specifically, changes in landscape pattern were simulated using a modeling platform that combines Geographic Information System (GIS) and Cellular Automaton (CA) modules. Experts in ecosystem conservation and management participated through surveys and workshops. Food, drinking water, service water, soil erosion control, water flow regulation, pollination/seed dispersal, regulation of macro climate, and landscape aesthetic/amenity were identified as the most relevant ES. Among the forest ecosystems, Páramo-related ecosystems were regarded to provide multiple ES with high capacities. Compared to the current status, the deforestation scenario showed to decrease most BES by 20–25 %, while increasing food provision by 5 %, as a trade-off. Regarding the climate change scenarios, the “Representative Concentration Pathways” (RCP) by 2070 were simulated with an increase in temperature of 2 °C (RCP 2.6) and of 4 °C (RCP 6.0). RCP 6.0 showed more noticeable impact than RCP 2.6, which caused a decrease in most BES whereas an increase in food provision due to the possible expansion of arable land into higher altitudes. The results of the spatial assessment also indicated high and low potential areas for BES provision. Such information can support decision-making for BES management e.g., priority areas for actions. Furthermore, the applied spatially explicit assessment could be a starting point for a regular assessment of BES, which has not yet been implemented in Ecuador.

Selective Synthesis of Organonitrogen Compounds via Electrochemical C-N Coupling on Atomically Dispersed Catalysts.

The C-N coupling reaction demonstrates broad application in the fabrication of a wide range of high value-added organonitrogen molecules including fertilizers (e.g., urea), chemical feedstocks (e.g., amines, amides), and biomolecules (e.g., amino acids). The electrocatalytic C-N coupling pathways from waste resources like CO2, NO3-, or NO2- under mild conditions offer sustainable alternatives to the energy-intensive thermochemical processes. However, the complex multistep reaction routes and competing side reactions lead to significant challenges regarding low yield and poor selectivity toward large-scale practical production of target molecules. Among diverse catalyst systems that have been developed for electrochemical C-N coupling reactions, the atomically dispersed catalysts with well-defined active sites provide an ideal model platform for fundamental mechanism elucidation. More importantly, the intersite synergy between the active sites permits the enhanced reaction efficiency and selectivity toward target products. In this Review, we systematically assess the dominant reaction pathways of electrocatalytic C-N coupling reactions toward various products including urea, amines, amides, amino acids, and oximes. To guide the rational design of atomically dispersed catalysts, we identify four key stages in the overall reaction process and critically discuss the corresponding catalyst design principles, namely, retaining NOx/COx reactants on the catalyst surface, regulating the evolution pathway of N-/C- intermediates, promoting C-N coupling, and facilitating final hydrogenation steps. In addition, the advanced and effective theoretical simulation and characterization technologies are discussed. Finally, a series of remaining challenges and valuable future prospects are presented to advance rational catalyst design toward selective electrocatalytic synthesis of organonitrogen molecules.