Modeling Platform Research Articles

Firefighter helmets and cervical intervertebral Kinematics: An OpenSim-Based biomechanical study

The assessment of cervical intervertebral kinematics can serve as the basis for understanding any degenerative changes in the cervical spine due to the prolonged wear of a heavyweight, imbalanced firefighting helmet. Therefore, this study aimed to analyze cervical intervertebral kinematics using the OpenSim musculoskeletal modeling platform in order to provide much-needed insights into how the inertial properties of firefighter helmets affect cervical spinal mobility. A total of 36 firefighters (18 males and 18 females) were recruited to perform static and dynamic neck flexion, extension, and left and right lateral bending tasks for three conditions: 1) no-helmet, 2) US-style helmet with a comparatively superior center of mass (COM), and 3) European-style helmet with relatively higher mass but an inferior COM. Three custom-made OpenSim head-neck models were created to calculate cervical intervertebral kinematics for each helmet condition. Results showed that helmet use significantly (p < 0.001) affects neck and cervical spinal kinematics. Despite its lighter weight, the superior COM placement in the US-style helmet caused more pronounced angular changes and higher velocity of peak flexion and extension angles compared to the European-style helmet across all cervical joints. Moreover, results revealed discrepancies between OpenSim-derived neck and cervical range-of-motion and those reported in previous in-vivo studies. In conclusion, the present study underscores the importance of designing firefighter helmets with a lower profile (less superior COM) to enhance neck range of motion and minimize potential neck injuries.

The performance of artificial intelligence-based large language models on ophthalmology-related questions in Swedish proficiency test for medicine: ChatGPT-4 omni vs Gemini 1.5 Pro

PurposeTo compare the interpretation and response context of two commonly used artificial intelligence (AI)-based large language model (LLM) platforms to ophthalmology-related multiple choice questions (MCQs) in the Swedish proficiency test for medicine (“kunskapsprov för läkare”) exams. DesignObservational study. MethodsThe questions of a total of 29 exams held between 2016 and 2024 were reviewed. All ophthalmology-related questions were included in this study, and categorized into ophthalmology sections. Questions were asked to ChatGPT-4o and Gemini 1.5 Pro AI-based LLM chatbots in Swedish and English with specific commands. Secondly, all MCQs were asked again without feedback. As the final step, feedback was given for questions that were still answered incorrectly, and all questions were subsequently re-asked. ResultsA total of 134 ophthalmology-related questions out of 4876 MCQs were evaluated via both AI-based LLMs. The MCQ count in the 29 exams was 4.62 ± 2.21 (range: 0–8). After the final step, ChatGPT-4o achieved higher accuracy in Swedish (94 %) and English (95.5 %) compared to Gemini 1.5 Pro (both at 88.1 %) (p = 0.13, and p = 0.04, respectively). Moreover, ChatGPT-4o provided more correct answers in the neuro-ophthalmology section (n = 47) compared to Gemini 1.5 Pro across all three attempts in English (p<0.05). There was no statistically significant difference either in the inter-AI comparison of other ophthalmology sections or in the inter-lingual comparison within AIs. ConclusionBoth AI-based LLMs, and especially ChatGPT-4o, appear to perform well in ophthalmology-related MCQs. AI-based LLMs can contribute to ophthalmological medical education not only by selecting correct answers to MCQs but also by providing explanations.

Reconstructing of the geometry of Atg13 and Atg101 molecules while assembling the complex

Aim. Associated subproteins which constitute the ATG1 multi-protein complex in plants and mammals, including ULK1 in humans, are orchestral protein kinase atg-units in resistance to stress stimuli across their different nature. The goals of this endeavour were to characterize the molecular nature of the interaction of ATG13 with ATG101, followed by in silico docking to catch the plausible ensuing integration into a multimeric complex ULK1/ATG1, which initiates the assembly of a PAS-preautophagosomal structure in the first step of autophagy initiation. Methods. Protein structures were modeled by homology using AlphaFold, and molecular dynamics (MD) was performed using GROMACS 5.0 with the Charmm36. Results. By implementing computer modeling methods, a complex of protein kinase atg-units for both ATG13 and ATG101 proteins, reflecting the interaction interface and conformational properties, was constructed for detailed interpretation while forming the forthcoming assembly of the ULK1/ATG1 multi-protein platform. Conclusions. This study provides a high-quality model platform for further sequential studies of protein-protein docking and protein-protein interactions with the possibility of reconstructing a model of the full ULK1/ATG1 complex to identify ATG8 binding sites.

Modeling Muscle Activities of Squat Motion using OpenSIM

Human beings need to be able to monitor their muscle health. Muscle health can be assessed by directly measuring its signal using an electromyography sensor or, recently, from a musculoskeletal modeling software such as OpenSIM. OpenSIM is an open-source platform for modeling, simulating, and analyzing the neuromusculoskeletal system. This work aims to simulate muscle forces during squat movement using OpenSIM simulation and validate the results using electromyography sensors attached to the body. The squat movement data generated from the optical motion capture system and the force plate will be used as inputs for the OpenSIM software. OpenSIM can provide output, such as a graph of the working muscle forces. That graph will be compared and analyzed with a surface electromyography sensor results graph. Based on the analysis results, the chart of working muscle forces generated by the OpenSIM software has shown a similar trend to the graph of muscle activity resulting from surface electromyography sensor reading. Therefore, the simulation results from the OpenSIM software were validated, and it was implied that the data collection process and the modeling were done correctly.

Assessment of NSCLC disease burden: A survival model-based meta-analysis study

We present a meta-analytics approach to quantify NSCLC disease burden by integrative survival models. Aggregated survival data from public sources were used to parameterize the models for early as well as advanced NSCLC stages incorporating chemotherapies, targeted therapies, and immunotherapies. Overall survival (OS) was predicted in a heterogeneous patient cohort based on various stratifications and initial conditions. Pharmacoeconomic metrics (life years gained (LYG) and quality-adjusted life years (QALY) gained), were evaluated to quantify the benefits of specialized treatments and improved early detection of NSCLC. Simulations showed that the introduction of novel therapies for the advanced NSCLC sub-group increased median survival by 8.1 months (95 % CI: 5.9, 10.0), with corresponding gains of 2.9 months (95 % CI: 2.2, 3.6) in LYG and 1.65 months (95 % CI: 1.2, 2.0) in QALY. Scenarios representing improved detection of early cancer in the whole patient cohort, revealed up to 17.6 (95 % CI: 16.5, 19.0) and 15.7 months (95 % CI: 14.8, 16.6) increase in median survival, with respective gains of 6.2 months (95 % CI: 5.9, 6.4) and 5.2 months (95 % CI: 4.9, 5.4) in LYG and 6.6 months (95 % CI: 6.4, 6.7) and 6.0 months (95 % CI: 5.9, 6.2) in QALY for conventional and optimal treatment. This integrative modeling platform, aimed at characterizing cancer burden, allows to precisely quantify the cumulative benefits of introducing specialized therapies into the treatment schemes and survival prolongation upon early detection of the disease.

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.