A blended shifted-fracture/phase-field framework for sharp/diffuse crack modeling

This is the peer reviewed version of the following article: Li, K.; Rodriguez-Ferran, A.; Scovazzi, G. A blended shifted-fracture/phase-field framework for sharp/diffuse crack modeling. "International journal for numerical methods in engineering", 28 Febrer 2023, vol. 124, núm. 4, p. 998-1030, which has been published in final form at https://onlinelibrary.wiley.com/doi/10.1002/nme.7152. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.The shifted fracture method (SFM) is an embedded method that enables sharp crack representations while using mesh-fitted data structures. In the SFM, the true crack is embedded in the computational grid, but the crack interface conditions are approximated by, or shifted to, a surrogate crack composed of element boundaries (i.e., edges/faces in two/three dimensions). This avoids enriched degrees-of-freedom and cut elements, so that data structures and geometrical treatment are much simpler, while still maintaining mesh-independent and accurate crack approximations. This article presents a continuous-discontinuous model of fracture based on blending a phase-field (PF) model with the SFM. The PF tracks the evolution of cracks inside a numerical fracture processing zone: diffuse cracks initiate, propagate, branch, and merge according to the field equations of energy minimization; no ad-hoc criteria are needed. The PF damage variable is then used to define the geometry of the true crack. With computational efficiency in mind, the PF model is only solved in subdomains where additional crack growth is expected and the SFM representation is used elsewhere. The efficiency and accuracy of the proposed approach in capturing complex crack patterns are illustrated by a representative set of two-dimensional numerical examples.Peer ReviewedPostprint (author's final draft

Data augmentation for aspect-based sentiment analysis

In recent years, deep learning has been widely used in the field of natural language processing (NLP), achieving spectacular successes in various NLP tasks. These successes are largely due to its capability to automatically learn feature representations from text data. However, the performance of deep learning in NLP can be negatively affected by a lack of sufficiently large labeled corpus for training, resulting in limited improvement in performance. Data augmentation overcomes this small data problem by expanding the sample size for the classes of data in the training corpus. This paper introduces the data augmentation for aspect-based sentiment analysis (ABSA), a classical research topic in NLP that has been applied in various fileds. The study aims to enhance the classification performance of ABSA through various augmentation strategies. Two specific augmentation strategies are presented, part-of-speech (PoS) wise synonym substitution (PWSS) and dependency relation-based word swap (DRAWS), which augment data using PoS, external domain knowledge, and syntactic dependency. These strategies are evaluated through extensive experimentation on four public datasets using three representative deep learning models—aspect-specific graph convolutional network (ASGCN), content attention-based aspect-based sentiment classification (CABASC), and long short-term memory (LSTM) network. Compared with the results without data augmentation, our augmentation strategies achieve a performance gain of up to 11.49% on Macro-F1, with the lowest gain being 2.9%. The experimental results demonstrate that the proposed data augmentation strategies are very useful for training deep learning models on small data corpus.</p

Respiratory self-gating for free-breathing magnetization transfer MRI of the abdomen.

PurposeMagnetization transfer (MT) MRI can be effective for the diagnosis of a broad range of fibrotic diseases, including liver fibrosis. However, respiratory motion, a major source of artifacts in thoracic and abdominal MR imaging, can obscure important anatomic structures, making diagnosis difficult. In this study, we explored the potential to combine free-breathing (FB) respiratory self-gating (RSG) methods with MT saturation for FB MT ratio (MTR) measurements of abdominal organs.MethodsA respiratory self-gated multiple-gradient recalled echo sequence with MT presaturation (RSG-MT GRE) was developed and applied in a series of seven normal volunteers. We compared the MTR values of liver, pancreas, kidney, spleen, and posterior paraspinal muscle measured using our RSG-MT GRE sequence and a conventional MT GRE sequence.ResultsRSG consistently reduced motion artifacts within MT-weighted images acquired during FB, improved the accuracy of FB MTR measurements, and produced comparable MTRs to breath-holding MTR measurements.ConclusionRSG approaches may offer to improve the utility of MT-weighted imaging methods for the assessment of fibrotic diseases and tumor desmoplasia in abdominal organs

Tumoral angiogenesis in both adrenal adenomas and nonadenomas: a promising computed tomography biomarker for diagnosis.

To explore the correlation between the typical findings of dynamic contrast-enhanced computed tomography (DCE-CT) and tumoral angiogenesis (microvessel density [MVD] and vascular endothelial growth factor [VEGF]) in adenomas and nonadenomas such that the enhancement mechanism of DCE-CT in adrenal masses can be explained more precisely. Forty-two patients with 46 adrenal masses confirmed by surgery and pathology were included in the study; these masses included 23 adenomas, 18 nonadenomas, and 5 hyperplastic nodules. The findings of DCE-CT and angiogenesis in adrenal masses were studied. The features of DCE-CT in adenomas and nonadenomas were evaluated to determine whether the characteristics of DCE-CT in adrenal masses were closely correlated with tumoral angiogenesis. Adrenal adenomas were significantly different from nonadenomas in the time density curve and the mean percentage of enhancement washout at the 7-minute delay time in DCE-CT. The mean MVD and VEGF expression exhibited significant differences between the rapid washout group (types A and C) and the slow washout group (types B, D, and E) and between the relative washout (Washr) ≥34% and the absolute washout (Washa) ≥43% on the 7-minute enhanced CT scans (P=0.000). Adenomas were suggested when adrenal masses presented as types A and C, and/or the Washr ≥34%, and/or the Washa ≥43%, and the opposite was suggested for nonadenomas. These results showed a close correlation between the characteristics of DCE-CT and both MVD and VEGF expression in adrenal masses. There was also a significant difference in MVD and VEGF expression between adenomas and nonadenomas. In conclusion, MVD and VEGF expression are two important pathological factors that play important roles in the characterization of DCE-CT in adrenal masses because they cause different time density curve types, the Washr and the Washa for adrenal adenomas and nonadenomas

Tumoral angiogenesis in both adrenal adenomas and nonadenomas: a promising computed tomography biomarker for diagnosis

To explore the correlation between the typical findings of dynamic contrast-enhanced computed tomography (DCE-CT) and tumoral angiogenesis (microvessel density [MVD] and vascular endothelial growth factor [VEGF]) in adenomas and nonadenomas such that the enhancement mechanism of DCE-CT in adrenal masses can be explained more precisely. Forty-two patients with 46 adrenal masses confirmed by surgery and pathology were included in the study; these masses included 23 adenomas, 18 nonadenomas, and 5 hyperplastic nodules. The findings of DCE-CT and angiogenesis in adrenal masses were studied. The features of DCE-CT in adenomas and nonadenomas were evaluated to determine whether the characteristics of DCE-CT in adrenal masses were closely correlated with tumoral angiogenesis. Adrenal adenomas were significantly different from nonadenomas in the time density curve and the mean percentage of enhancement washout at the 7-minute delay time in DCE-CT. The mean MVD and VEGF expression exhibited significant differences between the rapid washout group (types A and C) and the slow washout group (types B, D, and E) and between the relative washout (Washr) ≥34% and the absolute washout (Washa) ≥43% on the 7-minute enhanced CT scans (P=0.000). Adenomas were suggested when adrenal masses presented as types A and C, and/or the Washr ≥34%, and/or the Washa ≥43%, and the opposite was suggested for nonadenomas. These results showed a close correlation between the characteristics of DCE-CT and both MVD and VEGF expression in adrenal masses. There was also a significant difference in MVD and VEGF expression between adenomas and nonadenomas. In conclusion, MVD and VEGF expression are two important pathological factors that play important roles in the characterization of DCE-CT in adrenal masses because they cause different time density curve types, the Washr and the Washa for adrenal adenomas and nonadenomas

Arg-Gly-Asp-D-Phe-Lys peptide-modified PEGylated dendrimer-entrapped gold nanoparticles for targeted computed tomography imaging of breast carcinoma.

AimTo investigate cyclo (Arg-Gly-Asp-D-Phe-Lys) peptide (RGD)-modified PEGylated dendrimer-entrapped gold nanoparticles (PEGylated Au DENPs-RGD) for targeted computed tomography (CT) imaging of breast carcinomas.Materials &amp; methodsPEGylated Au DENPs-RGD were synthesized and characterized. Then, the PEGylated Au DENPs-RGD for targeted CT imaging were investigated using the MDA-MB-435 cell line, an integrin-rich breast carcinoma cells, and mice with MDA-MB-435 xenograft tumors. Finally, silver enhancement staining and integrin αvβ3 immunohistochemistry of the tumors were performed.ResultsThe synthesized PEGylated Au DENPs-RGD were spherical, water dispersible and biocompatible nanoprobes with a gold nanoparticle core size of 2.8 nm. Due to the presence of the Au nanoparticles, the PEGylated Au DENPs-RGD displayed a higher x-ray attenuation intensity than Omnipaque at the same Au or I concentrations. The conjugated RGD ligand can specifically identify and target overexpressed integrin receptors on MDA-MB-435 cells. After intravenous injection, these nanoprobes accumulated in the targeted area of mice with MDA-MB-435 xenograft tumors, which enabled the tumor to be detected by CT imaging. The histological results confirmed the imaging results.ConclusionThe PEGylated Au DENPs-RGD can be used as targeted nanoprobes with good biocompatibility for targeted CT imaging and diagnosis of integrin-positive tumors

Differentiation between adrenal adenomas and nonadenomas using dynamic contrast-enhanced computed tomography.

This study was performed to evaluate the findings including the time density curve (TD curve), the relative percentage of enhancement washout (Washr) and the absolute percentage of enhancement washout (Washa) at dynamic contrast-enhanced computed tomography (DCE-CT) in 70 patients with 79 adrenal masses (including 44 adenomas and 35 nonadenomas) confirmed histopathologically and/or clinically. The results demonstrated that the TD curves of adrenal masses were classified into 5 types, and the type distribution of the TD curves was significantly different between adenomas and nonadenomas. Types A and C were characteristic of adenomas, whereas types B, D and E were features of nonadenomas. The sensitivity, specificity and accuracy for the diagnosis of adenoma based on the TD curves were 93%, 80% and 87%, respectively. Furthermore, when myelolipomas were excluded, the specificity and accuracy for adenoma were 90% and 92%, respectively. The Washr and the Washa values for the adenomas were higher than those for the nonadenomas. The diagnostic efficiency for adenoma was highest at 7-min delay time at DCE-CT; Washr was more efficient than Washa. Washr ≥34% and Washa ≥43% were both suggestive of adenomas and, on the contrary, suspicious of nonadenomas. The sensitivity, specificity and accuracy for the diagnosis of adenoma were 84%, 77% and 81%, respectively. When myelolipomas were precluded, the diagnostic specificity and accuracy were 87% and 85%, respectively. Therefore, DCE-CT aids in characterization of adrenal tumors, especially for lipid-poor adenomas which can be correctly categorized on the basis of TD curve combined with the percentage of enhancement washout

Clinically applicable magnetic-labeling of natural killer cells for MRI of transcatheter delivery to liver tumors: preclinical validation for clinical translation.

AimTo test the hypothesis that MRI can monitor intraportal vein (IPV) transcatheter delivery of clinically applicable heparin-protamine-ferumoxytol (HPF) nanocomplex-labeled natural killer (NK) cells to liver tumor.Materials &amp; methodsLiver tumor rat models underwent catheterization for IPV infusion of HPF-labeled NK cells (NK-92MI cell line). MRI measurements within tumor and adjacent liver tissues were compared pre- and post-NK cell infusion. Histology studies were used to identify NK cells in the target tumors.ResultsFor first time, we demonstrated that MRI tracks HPF-labeled NK cells migration within liver following IPV delivery.ConclusionIPV transcatheter infusion permitted selective delivery of NK cells to liver tissues and MRI allowed tracking NK cell biodistributions within the tumors