3D Model Research Articles

FPGA Accelerated Implementation of 3D Mesh Secret Sharing Based on Symmetric Similarity of Model

Secret sharing is particularly important in the field of information security, which allows for the reconstruction of secret information from secure shares. However, due to the large amount of data and non-integer data type of 3D (three-dimensional) models, it is less efficient to perform sharing compared to the 2D(two-dimensional) digital images. In order to enable efficient sharing of 3D models as well, this article designs different circuit modules to parallelize the process of sharing 3D models. The proposed structure exploits the vertex extension to perform a complete reconstruction of the 3D model. In the sharing phase, the symmetric similarity of 3D model is exploited to realize the sharing in parallel, which improves the efficiency of sharing. In the reconstruction phase, the Strassen algorithm is used to optimize matrix multiplication, which saves circuit resources. Simulation results show that the structure performs more than 100 times faster than software. The utilization of circuit resources and the size of the share are both optimized. The validity of the designed hardware architecture is confirmed after analyzing the data from experiments performed on several 3D models.

Development of Mg‐Alginate Based Self Disassociative Bio‐Ink for Magnetic Bio‐Patterning of 3D Tumor Models

AbstractAlginate forms a hydrogel via physical cross‐linking with divalent cations. In literature, Ca2+ is mostly utilized due to strong interactions but additional procedures are required to disassociate Ca‐alginate hydrogels. On the other hand, Mg‐alginate hydrogels disassociate spontaneously, which might benefit certain applications. This study introduces Mg‐alginate as the main component of a bio‐ink for the first time to obtain 3D tumor models by magnetic bio‐patterning technique. The bio‐ink contains magnetic nanoparticles (MNPs) for magnetic manipulation, Mg‐alginate hydrogel as a sacrificial material, and cells. The applicability of the methodology is tested for the formation of 3D tumor models using HeLa, SaOS‐2, and SH‐SY5Y cells. Long‐term cultures are examined by Live/dead and MTT analysis and revealed high cell viability. Subsequently, Collagen and F‐actin expressions are observed successfully in 3D tumor models. Finally, the anti‐cancer drug Doxorubicin (DOX) effect is investigated on 3D tumor models, and IC50 values is calculated to assess the drug response. As a result, significantly higher drug resistance is observed for bio‐patterned 3D tumor models up to tenfold compared to 2D control. Overall, Mg‐alginate hydrogel is successfully used to form bio‐patterned 3D tumor models, and the applicability of the model is shown effectively, especially as a drug screening platform.

Implementation of augmented reality herbarium malangensis website tour to enhance conservation literacy

The biodiversity of Indonesia showed by the numerous of plant species, including one of the 89,326 species of spore plants. Along with the high diversity of various threat factors that will affect the status of a plant, knowledge about plants can be enhanced through conservation literacy using modern technology-based learning media, such as 3D modeling and augmented reality (AR) websites. AR acts as an interactive window that opens the view of conservation reality. The aim of this research is to produce a rare plant learning media product in the Bromo Tengger Semeru National Park that exists on the Malangensis Herbarium with the integration of 3D modeling websites. The method used is R&D, referring to the ADDIE model. The practicality test results obtained 91.54%, while the media effectiveness test showed with n-gain scores obtaining a result of 0.66 that media can improve conservation literacy skills in biology students of the State University of Malang. This research could provide a benchmark and literature for advanced media development on plant divisions other than Pteridophyte.

Three-dimensional tissue engineered skeletal muscle modelling facioscapulohumeral muscular dystrophy

Abstract Facioscapulohumeral muscular dystrophy (FSHD) is caused by sporadic misexpression of the transcription factor double homeobox 4 (DUX4) in skeletal muscles. So far, monolayer cultures and animal models have been used to study the FSHD disease mechanism and for FSHD therapy development, but these models do not fully recapitulate the disease and there is a lack of knowledge on how DUX4 misexpression leads to skeletal muscle dysfunction. To overcome these barriers, we have developed a three-dimensional tissue engineered skeletal muscle (3D-TESM) model by generating genetically matched myogenic progenitors (MPs) from human induced pluripotent stem cells of three mosaic FSHD patients. 3D-TESMs derived from genetically affected MPs recapitulate pathological features including DUX4 and DUX4 target gene expression, smaller myofiber diameters, and reduced absolute forces upon electrical stimulation. RNA sequencing data illustrates increased expression of DUX4 target genes in 3D-TESMs compared to two-dimensional (2D) myotubes, and cellular differentiation was improved by 3D culture conditions. Treatment of 3D-TESMs with three different small molecules identified in drug development screens in 2D muscle cultures showed no improvements, and sometimes even declines, in contractile force and sarcomere organization. These results suggest that these compounds either have a detrimental effect on the formation of 3D-TESMs, an effect that might have been overlooked or was challenging to detect in 2D cultures and in vivo models, and/or that further development of the 3D-TESM model is needed. In conclusion, we have developed a 3D skeletal muscle model for FSHD that can be employed for preclinical research focusing on DUX4 expression and downstream pathways of FSHD in relation to contractile properties. In the future, we expect that this model can also be used for preclinical drug screening.

A Study on the Attenuation Patterns of Underground Blasting Vibration and Their Impact on Nearby Tunnels

The natural caving method, as a new technique in underground mining, has been promoted and applied in several countries worldwide. The destruction of the bottom rock mass structure directly impacts the structural stability of underground engineering, resulting in damage and collapse of underground tunnels. Therefore, based on the principles of explosion theory and field monitoring data, a scaled three-dimensional numerical simulation model of underground blasting was constructed using LS-DYNA19.0 software to investigate the attenuation patterns of underground blasting vibrations and their impact on nearby tunnels. The results show that the relative error range between the simulated blasting vibration velocities based on the FEM-SPH (Finite Element Method–Smoothed Particle Hydrodynamics) algorithm and the measured values is between 7.75% and 9.85%, validating the feasibility of this method. Significant fluctuations in blasting vibration velocities occur when the blast center increases to within a range of 10–20 m. As the blast center distance exceeds 25 m, the vibration velocities are increasingly influenced by the surrounding stress. Additionally, greater stress results in higher blasting vibration velocities and stress wave intensities. Fitting the blasting vibration velocities of various measurement points using the Sadovsky formula yields fitting correlation coefficients ranging between 0.92 and 0.97, enabling the prediction of on-site blasting vibration velocities based on research findings. Changes in propagation paths lead to localized fluctuations in the numerical values of stress waves. These research findings are crucial for a deeper understanding of underground blasting vibration patterns and for enhancing blasting safety.

Unlocking the Potential of Pediatric Virtual Care: An e-Delphi Study on a Virtual Caregiver Participation Framework in Audiology

Purpose: Virtual service delivery models in audiology have become more accessible due to recent technological advancement and improved system-level uptake following COVID-19. Although current evidence identifies the benefits of virtual care to families with children who are d/Deaf or hard of hearing and supports its use in practice, this delivery model is still underutilized. This research aimed to gain consensus on an evidence-informed virtual caregiver participation framework developed from a scoping review of the communication sciences and disorders literature. Method: A two-round modified e-Delphi study was conducted to survey 26 knowledge users from four different countries with experience in virtual audiology care, including caregivers, audiologists, researchers, and organizational leaders. The study employed Delphi techniques, building from a scoping review to synthesize existing literature informing the knowledge gap, including online surveys and team discussions. Consensus was defined numerically (75% agreement) and by comparing and interpreting text-based responses. Results: The resulting framework grouped nine categories of caregiver participation in virtual care according to three main readiness domains: core readiness (opportunities to participate, perceived value, and willingness to participate), engagement readiness (child capacity, family–provider relationship, and role in the care process), and structural readiness (environment for participation, support, and technology). Conclusion: This work adds novel contributions to the field, through the development of a framework for caregiver participation in virtual audiology care, that can be used to support family involvement and will guide clinical tool development and future research efforts.

3D models related to the publication: 'Trophic differentiation between the endemic Cypriot mouse and the house mouse: a study coupling stable isotopes and morphometrics'

3D models related to the publication: 'Trophic differentiation between the endemic Cypriot mouse and the house mouse: a study coupling stable isotopes and morphometrics'

Developing a Virtual Model of the Rhesus Macaque Inner Ear

A virtual model of the rhesus macaque inner ear was created in the present study. Rhesus macaques have been valuable in cochlear research; however, their high cost prompts a need for alternative methods. Finite Element (FE) analysis offers a promising solution by enabling detailed simulations of the inner ear. This study employs FE analysis to create a virtual model of the rhesus macaque’s inner ear, reconstructed from MRI scans, to explore how cochlear implants (CIs) impact residual hearing loss. Harmonic-acoustic simulations of sound wave transmission indicate that CIs have minor effects on the displacement of the basilar membrane and thus minimally impact residual hearing loss post-implantation, but stiffening of the round window membrane worsens this effect. While the rhesus macaque FE model presented in this study shows some promise, its potential applications will require further validation through additional simulations and experimental studies.

Abstract B041: Investigating the impact of extracellular matrix stiffness on macrophage function and organoid growth in pancreatic ductal adenocarcinoma

Abstract Pancreatic ductal adenocarcinoma (PDAC) has a 5-year survival rate of only 11%. Current treatments mostly target the cancer cells themselves and have not been able to significantly improve survival rates, meaning there is an urgent need for novel therapies. PDAC is unique among solid tumors because it exhibits extensive desmoplasia that is characterized by an abundance of extracellular matrix (ECM) components. In recent years, an increasing body of work has shown that cancer tissue is stiffer than normal tissue by a factor of 3 or more. This increase in ECM stiffness has been shown to play an important role in affecting cell-to-cell communication as well as cancer progression and chemoresistance . However, how ECM stiffness affects tumor-associated macrophages, an important component of the pancreatic tumor microenvironment (TME), is still understudied. Previous studies have demonstrated that macrophages are highly responsive to mechanical cues, with the mechanical environment influencing macrophage polarization and function in a context- and disease-dependent manner. Elucidating these potential changes in PDAC can provide us with insights on how stiffness affects therapeutic outcome. Healthy pancreatic tissue typically exhibits a storage modulus of approximately 0.5-1 kPa, whereas PDAC tissue can range from 4-10 kPa. To study macrophage responses to varying stiffness, we cultured RAW264.7 mouse macrophage cell lines on 2D substrates with stiffness levels of 0.2, 2, and 8 kPa. We observed that macrophages cultured on stiffer matrices exhibited a trend toward a pro-inflammatory phenotype, with increased expression of M1 markers such as iNOS, IL-1β, and IL-6, compared to those cultured on softer matrices. However, conditioned media from macrophages cultured on both soft and stiff substrates similarly reduced the size of PDAC organoids, indicating a lack of functional difference between these groups. These findings suggest the need for more sophisticated models that better replicate the PDAC TME to fully capture the complex cell-to-cell interactions that are not evident in 2D cultures. To address this limitation, we developed a 3D tri-culture tunable biomimetic mouse model comprising PDAC organoids, host-matched cancer-associated fibroblasts (CAFs), and macrophages. This novel model allows us to modulate the stiffness of the 3D co-culture system through the addition of collagen I and CAFs. Rheometry data confirmed that the stiff tri-culture model had a significantly higher storage modulus than the soft tri-culture model. Using qPCR, we investigated the role of mechanosensitive ion channels, specifically Transient Receptor Potential Vanilloid-type 4 (TRPV4) and Piezo1, in mediating macrophage mechanosensing in response to varying levels of matrix stiffness. This study highlights the importance of 3D models that can recapitulate biophysical cues of cancer and will allow us to better understand how macrophages respond to stiffness, which may give rise to new therapeutic targets and development of new treatments in the future. Citation Format: Bayan Mahgoub, Weikun Xiao, Eileen Fung, Shannon Mumenthaler, Reginald Hill. Investigating the impact of extracellular matrix stiffness on macrophage function and organoid growth in pancreatic ductal adenocarcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B041.

Abstract C049: Implementing human bone marrow organoids to interrogate microenvironmental influences on the efficacy of blood cancer immunotherapies

Abstract Cancers perpetuate immunosuppressive niches that fuel progression and hinder the clinical utility of immunotherapies. Pre-clinical validation of immunotherapies often relies on 2D models that lack spatial complexity, or mouse models that do not fully recapitulate the human tumor microenvironment (TME). We recently developed a human induced pluripotent stem cell (iPSC)-derived bone marrow organoid platform, creating a robust system to interrogate cancer-stroma cross talk. Here, we further develop the model to create the first in vitro system for evaluation of blood cancer immunotherapies in a human tissue environment. We focused on targeting myeloproliferative neoplasms (MPNs) – chronic blood cancers affecting ∼400,000 individuals in the US that are currently largely incurable. 1/3 of MPNs are driven by a mutation in calreticulin (mutCALR), and the mutCALR oncoprotein is displayed on the cell surface of disease-initiating stem cells and fibrosis-driving megakaryocytes. MPNs are characterized by pronounced inflammation and fibrosis (“myelofibrosis”). Therapeutic antibodies have entered first-in-human trials, and we recently presented pre-clinical data for the first mutCALR-directed CAR-T cell therapy. However, it is unclear how the TME may limit the efficiency of these agents. To address this, we first tested the utility of the organoid platform to evaluate target killing of leukemic cell lines and cells from patients using the anti-CD33 antibody-drug conjugate (ADC) gemtuzumab. The ADC showed good penetration and potent target cell killing in organoids, with only minimal reduction in efficacy in TGFβ-rich/fibrotic microenvironments. We then developed more sophisticated ‘chimeroids’ comprising the iPSC organoid scaffold engrafted with malignant stem cells plus CAR-Ts. Addition of mutCALR-directed CAR-Ts induced highly selective killing of mutCALR+ stem/progenitor cells with minimal toxicity to non-malignant cells including niche cells (n=5 donors), replicating the highly specific and robust killing seen in 2D cultures. To evaluate the impact of TME perturbations on CAR-T phenotype and function, we generated a scRNAseq dataset of 161,970 cells from ‘healthy’ and ‘myelofibrotic’ organoids engrafted with patient-derived mutCALR+ cells plus CAR-Ts, pre-stimulating organoids with two immunoregulatory cytokines highly abundant in myelofibrosis -TGFβ and Galectin-1. CAR- Ts exposed to mutCALR+ cells showed a 2x expansion of CD8+ effector memory cells, with significant enrichment of IFNγ, TNFα and IL-2 signaling gene-sets. The proportion of immunosuppressive Tregs increased in a high TGFβ TME, but not with Galectin-1. Ongoing analyses are further interrogating crosstalk between CAR-T, target cells, and niche components, and exploring the pro-inflammatory impact of CAR-T killing on the marrow niche – a potential mediator of delayed hematopoietic recovery. These studies demonstrate the utility of human organoids to evaluate blood cancer-targeting immunotherapies within a relevant human TME, with broad relevance for mechanistic and translational studies. Citation Format: Zoë C. Wong, Yuqi Shen, Alex Rampotas, Isaac Gannon, Charlotte Brierley, Camelia Benlabiod, Nawshad Hayder, Eleanor Murphy, Aude-Anaïs Olijnik, Claire Roddie, Martin Pulé, Adam J. Mead, Abdullah O. Khan, Bethan Psaila. Implementing human bone marrow organoids to interrogate microenvironmental influences on the efficacy of blood cancer immunotherapies [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr C049.

Abstract A006: Investigating the effects of fibroblasts derived from the primary versus the metastatic organ on 3D biomimetic models of pancreatic cancer

Abstract Pancreatic ductal adenocarcinoma (PDAC) is the 3rd leading cause of cancer death in the United States with a 5-year survival rate of only 13%. Early diagnosis is very difficult and thus 53% of patients are diagnosed after metastasis has already occurred, with the liver being the most frequently affected site. Both primary tumors and metastases have dense desmoplastic stroma due to a high percentage of fibroblasts within the tumor microenvironment (TME). Previously, we developed a tunable 3D biomimetic model of the liver metastatic niche (LMN) to investigate how local fibroblasts affect tumor growth and chemoresistance in PDAC liver metastasis. This study aims to investigate the contributions of fibroblasts at the primary versus metastatic sites. We used matched primary PDAC and liver metastatic (LM) organoids derived from the Kras+/LSL-G12D; Trp53+/LSL-R172H; Pdx1-Cre (“KPC”) genetically engineered mouse model. This allows us to compare the effects of primary PDAC cancer associated fibroblasts (CAFs) and liver metastasis associated fibroblasts (MAFs) on tumor cell growth and chemoresistance. Rheometry analyses were conducted to study the impact of local fibroblasts on the extracellular matrix (ECM) stiffness. Our results showed that both storage and loss moduli were enhanced only when PDAC CAFs were present in the co-cultured gels compared to gels with MAFs. Additionally, the 3D biomimetic model showed fibroblasts increased tumor growth and chemoresistance to gemcitabine, only when they were derived from the same site as the tumor cells. This highlighted the importance of studying the organ-specific microenvironment to develop better treatment options for patients with metastatic PDAC. To delve deeper into the molecular basis of these observations, we conducted RNA-sequencing to identify and compare the gene expression profiles in primary and metastatic tumor organoids exposed to conditioned media from CAFs and MAFs using a transwell membrane co-culture model. Our results showed significant differences in gene expression based on the type of fibroblasts co-cultured with the organoids. Moreover, we investigated the role of MAF-derived exosomes on LM growth and chemoresistance using exosome depletion and direct exosome addition to LM organoids. Lastly, we performed exosomes size and distribution characterizations using dynamic light scattering (DLS) analysis. Taken together, these findings highlight the critical role of the organ-specific microenvironment in tumor progression and the necessity of targeted therapies to improve patient outcomes in metastatic PDAC. Our results underscore the importance of developing a tunable 3D biomimetic model of the LMN, as it enables the testing of novel therapeutic strategies designed to disrupt interactions between MAFs and tumor cells, and potentially advancing treatments for metastatic PDAC. Citation Format: Mahsa Pahlavanneshan, Weikun Xiao, Eileen Fung, Vaidhyanathan Mahaganapathy, Chae Young Eun, Chang-Il Hwang, Shannon Mumenthaler, Reginald Hill. Investigating the effects of fibroblasts derived from the primary versus the metastatic organ on 3D biomimetic models of pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr A006.

Abstract IA014: Unraveling pancreatic tumor defenses: inside the stromal orchestra with the HOST-factor

Abstract Dive into how members of the Cukierman lab and their collaborators explore desmoplasia, the dense “shield” around tumors. Discover their groundbreaking 3D model that reveals the intricate “symphony” of fibroblasts and the interstitial extracellular matrix they produce. Learn how these elements impact cancer cells, as well as the function of immune and other tumor microenvironment cells. Central to the lab’s research is the HOST-Factor (Harmonic Output of Stromal Traits), a new tool to measure and eventually modify the microenvironment’s influence on tumors. Don’t miss this opportunity to see how the team is transforming our understanding of pancreatic cancer’s onset, progression, and treatment responses. Citation Format: Edna Cukierman. Unraveling pancreatic tumor defenses: inside the stromal orchestra with the HOST-factor [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr IA014.

The Politics of Identity Markers: A Critical Discourse Analysis of Pakistani English Newspapers

This study looked at how politicians come about with their political identities using identity markers to communicate their ideology(s) and ideas in political discourse. This study attempted to examine such identifying markers employed by Imran Khan (PTI), Fazal-ur-Rehman (JUI-F), Nawaz Sharif (PML-N), and Bilawal Bhutto (PPP) in Dawn and The Express Tribune news between 2018 and 2023. Data was obtained from the sites of a number of newspapers using a qualitative research method, using Fairclough's 3D model. Important markers of identification were phrases such as youth, corruption, accountability, and Naya Pakistan (new Pakistan), as well as cultural symbols, like flags and turbans. The ongoing use of pronouns, metaphors, and authoritative language by politicians helped to make societal topics such as power dynamics, corruption, and development lively. It is found that Fairclough's approach to the analysis of political identity markers can be put to good use.

PLLA Porous Scaffold as a 3D Breast Cancer Model to Investigate Drug Resistance.

Multidrug resistance remains one of the major challenges in breast cancer research, often leading to treatment failure. To better understand this mechanism, sophisticated three-dimensional (3D) tumor models are necessary, as they offer several advantages over traditional bidimensional (2D) cultures. In this study, poly-l-lactic-acid porous scaffolds were produced using a thermally induced phase separation technique and employed as 3D models for breast cancer cell lines: MDA-MB-231, MCF-7, and its multidrug-resistant variant, MCF-7R. The MTS assay was used to compare growth inhibition following doxorubicin treatment in 2D and 3D. Remarkably, the IC50 values increased in 3D cultures compared to 2D: MDA-MB-231 (445 vs. 54.5 ng/mL), MCF-7 (7.45 vs. 0.75 μg/mL), and MCF-7R (165 vs. 39 μg/mL). MCF-7R, which usually shows greater resistance in 2D, demonstrated even higher resistance in 3D. In fact, IC50 was not reached within 3 days as with the other models, but only after 6 days. Cellular morphology also played a crucial role. When treated with concentrations higher than the IC50, MDA-MB-231 cells lost their physiological 3D clustered structure, while MCF-7 and its resistant variant exhibited disrupted layers. All cell lines in 3D showed higher chemoresistance, suggesting a more biomimetic spatial architecture. Our work bridges the gap between monolayer and animal models, highlighting the potential of polymeric 3D scaffolds in breast cancer research.

Probing the Interplay of Protein Self-Assembly and Covalent Bond Formation in Photo-Crosslinked Silk Fibroin Hydrogels.

Covalent crosslinking of silk fibroin via native tyrosine residues has been extensively explored; however, while these materials are very promising for biomedical, optical, soft robotics, and sensor applications, their structure and mechanical properties are unstable over time. This instability results in spontaneous silk self-assembly and stiffening over time, a process that is poorly understood. This study investigates the interplay between self-assembly and di-tyrosine bond formation in silk hydrogels photo-crosslinked using ruthenium (Ru) and sodium persulfate (SPS) with visible light. The effects of silk concentration, molecular weight, Ru/SPS concentration, and solvent conditions are examined. The Ru/SPS system enables rapid crosslinking, achieving gelation within seconds and incorporating over 90% of silk into the network, even at very low protein concentrations (≥0.75%wt/v). A model emerges where silk self-assembly both before and after crosslinking affects protein phase separation, mesoscale structure, and dynamic changes in the hydrogel network over time. Silk concentration has the greatest impact on hydrogel properties, with higher silk concentration hydrogels experiencing two orders of magnitude increase in stiffness within 1 week. This new understanding and ability to tune hydrogel properties and dynamic stiffening aids in developing advanced materials for 4D biofabrication, sensing, 3D cancer models, drug delivery, and soft robotics.

Neural network–based transfer learning to improve stiffness modeling of industrial robots with small experimental data sets

AbstractStiffness modeling is an essential subject for the composition of robot control. Accurate stiffness modeling is helpful for improving the control accuracy of industrial robots, particularly under dynamic load circumstances. The classic virtual joint modeling (VJM) method is challenging in predicting the deformation of the end-effector throughout the full workspace due to the nonlinear deformation of the robot joint and its serial articulated structure. This paper proposes a full-space stiffness modeling method for robots based on the integration of a multi-layer perceptual (MLP) model and VJM. To provide enough training data for the MLP model, VJM is used to build a stiffness model with a small set of experimental data to generate 106,400 training data. A model-based transfer learning approach is proposed to improve the model’s accuracy and generalization regarding the difference between generated training data and actual experimental data. The VJM stiffness model is compared with the MLP stiffness model and the existing CNN-based transfer learning model based on the same experimental data. Considering the deformation prediction in the three directions in Cartesian space, the mean absolute error, standard deviation, and maximum error of the MLP model are decreased by at least 24.90%, 14.20%, and 8.50%, respectively, than the VJM. These prediction results demonstrate that the proposed modeling technique can significantly increase the accuracy of robot stiffness modeling, which is essential for position compensation in precise motion control of robots under dynamic load.

Multicellular 3D models to study myocardial ischemia–reperfusion injury

Coronary heart disease is a major global health threat, with acute myocardial ischemia–reperfusion injury (IRI) being a major contributor to myocardial damage following an ischemic event. IRI occurs when blood flow to ischemic tissues is restored and exacerbates the cellular damage caused by ischemia/hypoxia. Although animal studies investigating IRI have provided valuable insights, their translation into clinical outcomes has been limited, and translation into medical practice remains cumbersome. Recent advancements in engineered three-dimensional human in vitro models could offer a promising avenue to bridge the “therapeutic valley of death” from bench to bedside, enhancing the understanding of IRI pathology. This review summarizes the current state-of-the-art cardiovascular 3D models, including spheroids, organoids, engineered cardiac microtissues, and organ-on-a-chip systems. We provide an overview of their advantages and limitations in the context of IRI, with a particular emphasis on the crucial roles of cell–cell communication and the multi-omics approaches to enhance our understanding of the pathophysiological processes involved in IRI and its treatment. Finally, we discuss currently available multicellular human 3D models of IRI.

Extension of a 3D Geological Entity Modeling Method for Discontinuous Deformation Analysis

AbstractWith the development of 3D discontinuous deformation analysis (DDA) in precise stress fields and crack propagation problems, it has also demonstrated outstanding capabilities in solving continuous–discontinuous problems. However, currently, 3D DDA modeling primarily focuses on generating rock joint networks and developing 3D cutting algorithms. Correspondingly, 3D geological modeling methods are not yet mature, and establishing 3D models often demands substantial time. The lack of supporting preprocessing modeling methods and corresponding visual operation interfaces significantly hampers the development of 3D DDA. This method builds upon advanced research achievements in unmanned aerial vehicle oblique photography, 3D reconstruction, 3D cutting, computer graphics, and visualization program design. This research establishes a 3D geological entity modeling method for 3D DDA and constructs a comprehensive program using relevant C++ libraries and C language interfaces. In this method, a 3D geological model that incorporates geological elements such as strata and faults is initially established using non‐uniform rational B‐splines (NURBSs) surfaces as the boundary of the solid model. Subsequently, finite element meshing is applied, followed by corresponding topology transformation, resulting in a 3D block system model suitable for 3D DDA calculation. To cater for diverse application scenarios, continuous–discontinuous models integrated with subblocks and models of arbitrary polyhedra can be established. The proposed method has been validated through several typical modeling examples, showing its ability to rapidly and generate 3D high‐precision geological reality models suitable for 3D DDA calculations. Additionally, some techniques used in this method can be extended for modeling other numerical simulation methods, warranting further research.

A Comparative Analysis of Bhumija-Style Gondeshwar Temple’s Acoustic Characteristics with Hemadpanti-Style Temples

ABSTRACT The study of the Hindu temple’s acoustics, acoustic characteristics, sound quality for clarity of music and speech intelligibility, and other applicable acoustic parameters must be addressed more in the literature. This study has conducted field measurements in Bhumija-style Gondeshwar temples in Nashik district, India. The temple has a distinctive tiered domed concave ceiling design in the pavilion and sanctum space and unique acoustic properties shaped by its architectural features. The research aims to report and investigate the acoustic characteristics through the well-known Impulse Response (IR) method to investigate empty temple conditions. A 3D model was imported and calibrated in ODEON 12.10 to compare scenarios when the worshippers were 100% present in the temple for various musical and chanting activities. Objective room-acoustic parameters such as Early Decay Time (EDT), Reverberation Time (T30), Clarity of Music (C80), Definition (D50), and Speech Transmission Index (STI) were measured and analyzed. The field measurements were also compared with previously studied Hemadpanti-style Hindu temples, such as the Markanda and Mrikunda temples. The results indicated that the tiered ceiling in Hemadpanti temples indicates a balance and moderate T30 values for all frequency ranges, as compared to the tiered concave domed ceiling in Bhumija-style Gondeshwar temple with higher T30 values observed at the lower frequency.

Influence of Specimen Width on Crack Propagation Process in Lightly Reinforced Concrete Beams

Models used to study the fracture process of concrete are often considered 2D, ignoring the influence of specimen width. However, during the fracture process in pre-cracked concrete beams, the crack length varies along the thickness direction, especially in reinforced concrete. To study the influence of specimen width on reinforced concrete fracture behavior, a 3D numerical method was used to simulate the crack propagation processes of lightly reinforced concrete beams based on Fracture Mechanics. Nonlinear spring elements with different stress-displacement constitutive laws were employed to characterize the softening behavior of concrete and the bond-slip behavior between the steel bars and concrete, respectively. It is assumed that the crack begins to propagate when the maximum stress intensity factor at the crack tip along the beam width reaches the initial fracture toughness of concrete. To verify the validity of the proposed method, the completed crack propagation processes of lightly reinforced concrete three-point bending notched beams were simulated, and the calculated load-crack mouth opening displacement curves showed a reasonable agreement with the experimental data. Moreover, the impact of the 2D reinforced concrete beam model on the crack propagation process was analyzed. The results indicate that at the initial loading stage, the external load P obtained from the 2D model is significantly larger than the result from the presented 3D model.