Detailed Model Research Articles

Development of patient-specific finite element model for study of composite dental implants

Traumatic dental injuries can occur due to various reasons such as accidents, sports injuries, fights, falls, and others. These injuries can affect the teeth, gums, and surrounding tissues, and can range from minor chips and cracks to severe fractures, dislocations, and avulsions (when the tooth is completely knocked out of the socket). The most common way to address this is by replacing affected teeth with dental implants. The purpose of this research is to evaluate the use of composite materials in dental implants and compare them with the traditionally used materials using a patient specific cone beam computed tomography (CBCT) based finite element model (FEM). To conduct this research, two different implant groups i.e., traditional implant and composite implant were designed using Titanium grade 4, zirconium oxide-reinforced lithium silicate (ZLS), and Zirconia (ZrO2). Six dental implants were designed namely Ti implant, ZLS implant, ZrO2 implant, Ti-ZrO2 composite, Ti-ZLS composite, and ZLS-ZrO2 composite using 3D modelling software. Detailed full-scale 3D models of patient specific dental implant were developed and traumatic loading conditions were applied to the enamel of central incisor teeth or crown of dental implant, and maxilla was constrained in all directions. It was found that the use of composite materials for dental implants can reduce the stresses over the surface of abutment and implant as compared to traditional implants. The detailed models developed as a part of this study can advance the research on dental implants, and with further experimental validation allow the use of composite materials for fabrication of more stable dental implants.

Anisotropic temperatures in multi-layered 2D materials

For multi-layered 2D materials, although its c-axis has a much lower thermal conductivity than the a-axis, its phonon mean free path has been confirmed to be very long, e.g., in the order of 100s nm at room temperature for multi-layered graphene. An anisotropic specific heat concept has been proposed in the past to explain this very long mean free path. This work carries out detailed atomistic modeling to quantify the anisotropic specific heat concept and reports the discovery of anisotropic temperatures in multi-layered 2D materials under ultrafast surface heating. Extremely fast c-phonon energy transport is discovered, and the non-Fourier effect is observed for both a-phonons and c-phonons. The energy coupling factor between these two modes of phonons is determined to be in the order of 1016 W K−1 m−3, with the specific number depending on the structure location. The anisotropic temperature concept is also quantitatively confirmed based on the lattice Boltzmann method simulation. The anisotropic temperature concept does not violate the physics that temperature is a scalar; rather, it is developed to distinguish the temperatures of phonons that travel in different directions. This concept is universally applicable to other 2D materials to describe the heat conduction in the in-plane and out-of-plane directions that feature different interatomic bonds.

INVISIBLE 2.0: An enhanced interference-based handover technique for visible light communications in vehicular networks

Since the last decade, Visible Light Communication (VLC) has represented a huge capacity to complement conventional Radio Frequency (RF) technologies in plenty of applications. The credibility of VLC in terms of power consumption has always been compared to RF. In this work, in addition to addressing this issue through a detailed power model, the co-existence of VLC and the Long-Term Evolution (LTE) cellular network in a vehicular environment has been empirically investigated. The coordination of data transmission among different technologies is managed through a novel vertical handover mechanism, namely INVISIBLE 2.0. This technique is triggered by the error probability to meet the 3GPP requirements on packet reception ratio while endorsing VLC as the preferred technology bearer. We demonstrate that INVISIBLE 2.0 achieves a more stable latency, and energy efficiency based on extensive simulation results.

Subject-specific finite element head models for skull fracture evaluation-a new tool in forensic pathology.

Post-mortem computed tomography (PMCT) enables the creation of subject-specific 3D head models suitable for quantitative analysis such as finite element analysis (FEA). FEA of proposed traumatic events is an objective and repeatable numerical method for assessing whether an event could cause a skull fracture such as seen at autopsy. FEA of blunt force skull fracture in adults with subject-specific 3D models in forensic pathology remains uninvestigated. This study aimed to assess the feasibility of FEA for skull fracture analysis in routine forensic pathology. Five cases with blunt force skull fracture and sufficient information on the kinematics of the traumatic event to enable numerical reconstruction were chosen. Subject-specific finite element (FE) head models were constructed by mesh morphing based on PMCT 3D models and A Detailed and Personalizable Head Model with Axons for Injury Prediction (ADAPT) FE model. Morphing was successful in maintaining subject-specific 3D geometry and quality of the FE mesh in all cases. In three cases, the simulated fracture patterns were comparable in location and pattern to the fractures seen at autopsy/PMCT. In one case, the simulated fracture was in the parietal bone whereas the fracture seen at autopsy/PMCT was in the occipital bone. In another case, the simulated fracture was a spider-web fracture in the frontal bone, whereas a much smaller fracture was seen at autopsy/PMCT; however, the fracture in the early time steps of the simulation was comparable to autopsy/PMCT. FEA might be feasible in forensic pathology in cases with a single blunt force impact and well-described event circumstances.

Detailed kinetics modeling of sulfur species evolution in alternating reducing/oxidizing atmosphere

Under conditions of deep load fluctuation, the furnace of a coal-fired boiler experiences alternating reduction/oxidation atmospheres, which directly impact the evolution of sulfur species. Building upon our previous mechanism (Model I), this study specifically considered the influence of alternating atmospheres and proposed a comprehensive reaction model (Model II), incorporating 8 additional elementary reactions. The relative error in predicting the concentration distribution of sulfur species was reduced from 18% (Model I) to 13% (Model II). In the alternating atmospheres, the predominant sulfur species remained as SO2 and H2S. Sensitivity analysis revealed that S, SH, SO, HSO, and HOSO were the critical free radicals. The new supplementary reactions (118) H2S + M = SH + H + M and (116) H2S + O2=HSO + OH played a significant role in the generation and consumption of H2S and SO2. Rate of production analysis demonstrated that the alternating atmosphere impacted the production and consumption primary free radicals like O/H/OH, thus potentially causing changes of S, SH, SO, HSO, and HOSO; moreover, it introduced new reaction pathways for SH and SO. Finally, a simplified reaction pathway for the sulfur species evolution was proposed. This study seeks to provide insights into the sulfur species evolution under the peak regulation conditions in coal-fired boilers.

Remote Rescue Vehicle

Search and rescue operations in collapsed buildings provide crucial challenges due to the complexity of the environment and the need for information about trapped individuals. This document presents a versatile system equipped with various sensors, including LiDAR, temperature, GPS, GSM, and Wi-Fi modules, designed to assist rescue teams. The system data collection capabilities include high-quality video, audio, and image formats that supplement situational awareness. The LiDAR sensor is used to create detailed 3D models and identify potential hazards and obstacles. The thermal sensor helps in the detection of temperature signatures and enables the identification of surviving or overheated machines. Additionally, the integration of the YOLO algorithm enables real-time object classification, providing critical insights for faster decision-making. The GSM module enables communication with the system. The Wi-Fi module enables high-speed data transmission to ensure that the collected information is quickly transmitted to the rescue team. High-quality video, audio, and image formats offer comprehensive situational awareness, support decision-making, and improve overall operational efficiency.

Performance analysis of electromagnetic vibration energy harvester under square excitation

Harvesting energy from surrounding vibrations is an effective method for powering various low-power electronic devices. The energy output performance of vibration energy harvesters under some special excitations remains to be investigated. In this paper, a vibration energy harvester (VEH) system based on a rack and pinion mechanism and a bevel gear set is proposed, and a detailed electromechanical coupling modeling of the system under general excitation and square wave excitation is carried out. The energy output characteristics of the proposed system under square wave excitation are explored through simulation and experiment. When the energy output is the target, the priority of adjusting the constituent parameters in the equivalent mass parameter, equivalent damping parameter and equivalent stiffness parameter of the system can be obtained based on the simulation results. The experimental results under periodic square wave excitation force show that the maximum output power of the proposed system is 2.7 W at an amplitude of 4 kN and a frequency of 3 Hz. This is a 55 % increase in the maximum power compared to the sinusoidal excitation under the same conditions. It is demonstrated that the proposed system has great potential to power various low-power electronic devices.

Reviving Antiquity in the Digital Era: Digitization, Semantic Curation, and VR Exhibition of Contemporary Dresses

In this paper, we present a comprehensive methodology to support the multifaceted process involved in the digitization, curation, and virtual exhibition of cultural heritage artifacts. The proposed methodology is applied in the context of a unique collection of contemporary dresses inspired by antiquity. Leveraging advanced 3D technologies, including lidar scanning and photogrammetry, we meticulously captured and transformed physical garments into highly detailed digital models. The postprocessing phase refined these models, ensuring an accurate representation of the intricate details and nuances inherent in each dress. Our collaborative efforts extended to the dissemination of this digital cultural heritage, as we partnered with the national aggregator in Greece, SearchCulture, to facilitate widespread access. The aggregation process streamlined the integration of our digitized content into a centralized repository, fostering cultural preservation and accessibility. Furthermore, we harnessed the power of these 3D models to transcend traditional exhibition boundaries, crafting a virtual experience that transcends geographical constraints. This virtual exhibition not only enables online exploration but also invites participants to immerse themselves in a captivating virtual reality environment. The synthesis of cutting-edge digitization techniques, cultural aggregation, and immersive exhibition design not only contributes to the preservation of contemporary cultural artifacts but also redefines the ways in which audiences engage with and experience cultural heritage in the digital age.

Intraoperative Videogrammetry and Photogrammetry for Photorealistic Neurosurgical 3-Dimensional Models Generated Using Operative Microscope: Technical Note.

Intraoperative orientation during microsurgery has a prolonged learning curve among neurosurgical residents. Three-dimensional (3D) understanding of anatomy can be facilitated with realistic 3D anatomic models created from photogrammetry, where a series of 2-dimensional images is converted into a 3D model. This study implements an algorithm that can create photorealistic intraoperative 3D models to exemplify important steps of the operation, operative corridors, and surgical perspectives. We implemented photograph-based and video-based scanning algorithms for uptakes using the operating room (OR) microscope, targeted for superficial structures, after surgical exposure, and deep operative corridors, in cranial microsurgery. The algorithm required between 30-45 photographs (superficial scanning), 45-65 photographs (deep scanning), or approximately 1 minute of video recording of the entire operative field to create a 3D model. A multicenter approach in 3 neurosurgical departments was applied to test reproducibility and refine the method. Twenty-five 3D models were created of some of the most common neurosurgical approaches-frontolateral, pterional, retrosigmoid, frontal, and temporal craniotomy. The 3D models present important steps of the surgical approaches and allow rotation, zooming, and panning of the model, enabling visualization from different surgical perspectives. The superficial and medium depth structures were consistently presented through the 3D models, whereas scanning of the deepest structures presented some technical challenges, which were gradually overcome with refinement of the image capturing process. Intraoperative photogrammetry is an accessible method to create 3D educational material to show complex anatomy and demonstrate concepts of intraoperative orientation. Detailed interactive 3D models, displaying stepwise surgical case-based anatomy, can be used to help understand details of the operative corridor. Further development includes refining or automatization of image acquisition intraoperatively and evaluation of other applications of the resulting 3D models in training and surgical planning.

Evolutionary novelties underlie sound production in baleen whales.

Baleen whales (mysticetes) use vocalizations to mediate their complex social and reproductive behaviours in vast, opaque marine environments1. Adapting to an obligate aquatic lifestyle demanded fundamental physiological changes to efficiently produce sound, including laryngeal specializations2-4. Whereas toothed whales (odontocetes) evolved a nasal vocal organ5, mysticetes have been thought to use the larynx for sound production1,6-8. However, there has been no direct demonstration that the mysticete larynx can phonate, or if it does, how it produces the great diversity of mysticete sounds9. Here we combine experiments on the excised larynx of three mysticete species with detailed anatomy and computational models to show that mysticetes evolved unique laryngeal structures for sound production. These structures allow some of the largest animals that ever lived to efficiently produce frequency-modulated, low-frequency calls. Furthermore, we show that this phonation mechanism is likely to be ancestral to all mysticetes and shares its fundamental physical basis with most terrestrial mammals, including humans10, birds11, and their closest relatives, odontocetes5. However, these laryngeal structures set insurmountable physiological limits to the frequency range and depth of their vocalizations, preventing them from escaping anthropogenic vessel noise12,13 and communicating at great depths14, thereby greatly reducing their active communication range.

Observation of Damage Initiation for Trans-laminar Fracture Using in situ Fast Synchrotron X-ray Radiography and ex situ X-ray Computed Tomography

AbstractTrans-laminar fracture is an important topic for engineering composites. In this study, trans-laminar fracture initiation in quasi-isotropic carbon/epoxy laminates made of non-crimp fabrics was examined using in situ fast synchrotron X-ray radiography and ex situ X-ray computed tomography. The maximum split lengths were measured by in situ radiography and were compared with the predicted values in a detailed FE model using cohesive elements. Ex situ computed tomography scans were also conducted to confirm that no fibre breakage occurs before the final load drop in the experiments. In situ and ex situ observations are complementary for the understanding of damage initiation.

Deep learning based approaches from semantic point clouds to semantic BIM models for heritage digital twin

This study focuses on the application of deep learning for transforming semantic point clouds into semantic Building Information Models (BIM) to create a Heritage Digital Twin, centering on Taoping Village, a site of historical and cultural significance in Sichuan, China. Utilizing advanced technologies such as unmanned aerial vehicles and terrestrial laser scanning, we capture detailed point cloud data of the village. A pivotal element of our methodology is the KP-SG neural network, which exhibits outstanding overall performance, particularly excelling in accurately identifying 11 categories. Among those categories, buildings and vegetation, achieves recognition rates of 81% and 83% respectively, and a 2.53% improvement in mIoU compared to KP-FCNN. This accuracy is critical for constructing detailed and accurate semantic BIM models of Taoping Village, facilitating comprehensive architecture and landscape analysis. Additionally, the KP-SG’s superior segmentation capability contributes to the creation of high-fidelity 3D models, enriching virtual reality experiences. We also introduce a digital twin platform that integrates diverse datasets, their semantic information, and visualization tools. This platform is designed to support process automation and decision-making and provide immersive experiences for tourists. Our approach, integrating semantic BIM models and a digital twin platform, marks a significant advancement in preserving and understanding traditional villages like Taoping and demonstrates the transformative potential of deep learning in cultural heritage conservation.

Power-to-X strategies for Smart Energy Regions: a vision for green hydrogen valleys

Future energy systems will have to face the challenge of managing surplus electricity from renewable sources. In this context, technologies like electrolyzers could play a key role since they can convert this surplus into hydrogen. The study aims to develop an energy strategy for the Campania region, in Italy, aligning with 2050 European CO2 reduction targets. It utilizes detailed bottom-up modeling and dynamic simulations to propose a scenario emphasizing extensive integration of renewable energy sources, particularly using Power-to-Gas technologies to convert surplus electricity into hydrogen for the transportation sector. This approach leads to abating the significant surplus of around 2.4 TWh/year produced by renewables and enables it to cover about 10% of transport sector consumption by hydrogen, boosting the overall share of renewable energy.

Modulation Techniques and Coordinated Voltage Vector Distribution: Effects on Efficiency in Dual-Inverter Topology-Based Electric Drives

The increasing popularity of electric drives employing an isolated dual-inverter (DI) topology is motivated by their superior DC-link voltage and power utilization, fault-tolerant operation, and potential for multilevel operation. These attributes are significant in battery-powered transportation, such as electric vehicles and aviation. Given the considerable freedom in modulation and control of the DI topology, this paper researches the impact of reference voltage vector distribution between the two individual inverters. The study also evaluates the influence of two well-established asynchronous modulation strategies—Space Vector PWM (SVPWM) and Depenbrock’s Discontinuous Modulation (DPWM1). Since simulation tools nowadays play a crucial role in power electronics design and concept verification, the results are based on extensive and detailed models in Matlab/Simulink. Employing the basic field-oriented control of a 12 kW induction motor with precisely parameterized SiC switching devices for accurate loss calculation, this research reveals the possibility of significant energy savings at multiple operating points. Notably, optimal efficiency is achieved when one inverter operates up to half of the nominal speed while the other solely establishes a neutral point for the winding. Moreover, the results highlight DPWM1 as a superior strategy for the DI topology, showcasing reduced converter losses. Overall, it is shown that the system’s losses can be significantly reduced just by the design of the voltage vector distribution in the drive’s operating range and the modulation strategy selection.

Reusable formal models for concurrency and communication in custom real-time operating systems

In embedded systems, the execution semantics of the real-time operating system (RTOS), which is responsible for scheduling and timely execution of concurrent processes, is crucial for the correctness of the overall system. However, existing approaches for the formal verification of embedded systems typically abstract from the RTOS completely, or provide a detailed and synthesizable formal model of the RTOS. While the former may lead to unsafe systems, the latter is not compatible with industrial design processes. In this paper, we present an approach for reusable abstract formal models that can be configured for custom RTOS. Our key idea is to formally capture common execution mechanisms of RTOS like preemptive scheduling, event synchronization, and communication abstractly in configurable timed automata models. These abstract formal models can be configured for a concrete custom RTOS, and they can be combined into a formal system model together with a concrete application. Our reusable models significantly reduce the manual effort of defining a formal model that captures concurrency and real-time behavior, together with the functionality of an application. The resulting formal model enables analysis, verification, and graphical simulation. We validate our approach by formalizing and analyzing a rescue robot application running the custom open source RTOS EV3RT.

The effect of yaw damper performance degradation on carbody hunting of high-speed trains

The yaw damper is an integral and pivotal component in guaranteeing the carbody hunting stability of high-speed trains (HSTs). However, it is reported that the occurring incidences of low-frequency carbody hunting frequently have been observed in HSTs, a predicament attributed to the degradation of yaw damper performance resulting from the obstruction of the damping valve by foreign particulates. Given these circumstances, the objective of this study is to investigate the impact of yaw damper performance degradation on the intricate phenomenon of carbody hunting motion. A HST dynamic model is developed, incorporating a detailed physical parameter model of the yaw damper, which enables the reproduction of abnormal low-frequency swaying arising from the deterioration in yaw damper performance. The findings of this study demonstrate that the obstruction of the damping valve significantly augments the damping force and dynamic stiffness of the yaw damper, thereby potentially instigating the occurrence of severe low-frequency hunting motion and consequent deterioration in the ride comfort of HSTs.

Programmable nanowrinkle-induced room-temperature exciton localization in monolayer WSe2

Localized states in two-dimensional (2D) transition metal dichalcogenides (TMDCs) have been the subject of intense study, driven by potential applications in quantum information science. Despite the rapidly growing knowledge surrounding these emitters, their microscopic nature is still not fully understood, limiting their production and application. Motivated by this challenge, and by recent theoretical and experimental evidence showing that nanowrinkles generate strain-localized room-temperature emitters, we demonstrate a method to intentionally induce wrinkles with collections of stressors, showing that long-range wrinkle direction and position are controllable with patterned array design. Nano-photoluminescence (nano-PL) imaging combined with detailed strain modeling based on measured wrinkle topography establishes a correlation between wrinkle properties, particularly shear strain, and localized exciton emission. Beyond the array-induced wrinkles, nano-PL spatial maps further reveal that the strain environment around individual stressors is heterogeneous due to the presence of fine wrinkles that are less deterministic. At cryogenic temperatures, antibunched emission is observed, confirming that the nanocone-induced strain is sufficiently large for the formation of quantum emitters. At 300 K, detailed nanoscale hyperspectral images uncover a wide range of low-energy emission peaks originating from the fine wrinkles, and show that the states can be tightly confined to regions <10 nm, even in ambient conditions. These results establish a promising potential route towards realizing room temperature quantum emission in 2D TMDC systems.

Robust and consistent measures of pattern separation based on information theory and demonstrated in the dentate gyrus.

Pattern separation is a valuable computational function performed by neuronal circuits, such as the dentate gyrus, where dissimilarity between inputs is increased, reducing noise and increasing the storage capacity of downstream networks. Pattern separation is studied from both in vivo experimental and computational perspectives and, a number of different measures (such as orthogonalisation, decorrelation, or spike train distance) have been applied to quantify the process of pattern separation. However, these are known to give conclusions that can differ qualitatively depending on the choice of measure and the parameters used to calculate it. We here demonstrate that arbitrarily increasing sparsity, a noticeable feature of dentate granule cell firing and one that is believed to be key to pattern separation, typically leads to improved classical measures for pattern separation even, inappropriately, up to the point where almost all information about the inputs is lost. Standard measures therefore both cannot differentiate between pattern separation and pattern destruction, and give results that may depend on arbitrary parameter choices. We propose that techniques from information theory, in particular mutual information, transfer entropy, and redundancy, should be applied to penalise the potential for lost information (often due to increased sparsity) that is neglected by existing measures. We compare five commonly-used measures of pattern separation with three novel techniques based on information theory, showing that the latter can be applied in a principled way and provide a robust and reliable measure for comparing the pattern separation performance of different neurons and networks. We demonstrate our new measures on detailed compartmental models of individual dentate granule cells and a dentate microcircuit, and show how structural changes associated with epilepsy affect pattern separation performance. We also demonstrate how our measures of pattern separation can predict pattern completion accuracy. Overall, our measures solve a widely acknowledged problem in assessing the pattern separation of neural circuits such as the dentate gyrus, as well as the cerebellum and mushroom body. Finally we provide a publicly available toolbox allowing for easy analysis of pattern separation in spike train ensembles.

Generation of a Digital Terrain Model (DTM) Fusioning WV-2 Images and RTK-derived Topobathymetric Data

Digital terrain models (DTMs) are digital elevation models (DEMs) that represent the bare ground surface. They are created by multiple sources, including satellite remote sensing, aerial photography, and ground-based surveys, and are often combined with other data sources to create highly detailed models. As the demand for accurate and detailed information about the Earth's surface continues to grow, DTMs have become an increasingly important tool for researchers in different fields. This study aims to create a DTM with a spatial resolution of 0.50 m for São Caetano do Sul, São Paulo, Brazil, integrated with a topobathymetric map of three water courses running along the borders of the study area. For the conventional DTM generation, a WV-2 stereo pair was used. A total of 55 ground control points (GCPs) were collected using the GNSS-RTK method, being 60% used for model building and 40% employed for validation. The topobathymetric survey was accomplished using a GNSS-RTK device placed along the analyzed open streams. For validation purposes, we used bias and MAE metrics. Overall, the methodology presented in this article provides a useful approach for generating high-resolution DTMs that can be used in a range of applications, especially in urban hydrodynamic studies.

Long-read sequencing reveals the structural complexity of genomic integration of HPV DNA in cervical cancer cell lines

BackgroundCervical cancer (CC) causes more than 311,000 deaths annually worldwide. The integration of human papillomavirus (HPV) is a crucial genetic event that contributes to cervical carcinogenesis. Despite HPV DNA integration is known to disrupt the genomic architecture of both the host and viral genomes in CC, the complexity of this process remains largely unexplored.ResultsIn this study, we conducted whole-genome sequencing (WGS) at 55-65X coverage utilizing the PacBio long-read sequencing platform in SiHa and HeLa cells, followed by comprehensive analyses of the sequence data to elucidate the complexity of HPV integration. Firstly, our results demonstrated that PacBio long-read sequencing effectively identifies HPV integration breakpoints with comparable accuracy to targeted-capture Next-generation sequencing (NGS) methods. Secondly, we constructed detailed models of complex integrated genome structures that included both the HPV genome and nearby regions of the human genome by utilizing PacBio long-read WGS. Thirdly, our sequencing results revealed the occurrence of a wide variety of genome-wide structural variations (SVs) in SiHa and HeLa cells. Additionally, our analysis further revealed a potential correlation between changes in gene expression levels and SVs on chromosome 13 in the genome of SiHa cells.ConclusionsUsing PacBio long-read sequencing, we have successfully constructed complex models illustrating HPV integrated genome structures in SiHa and HeLa cells. This accomplishment serves as a compelling demonstration of the valuable capabilities of long-read sequencing in detecting and characterizing HPV genomic integration structures within human cells. Furthermore, these findings offer critical insights into the complex process of HPV16 and HPV18 integration and their potential contribution to the development of cervical cancer.