bluuebunny/crossref_metadata_2025_split huggingface dataset:
Probabilistic Fatigue Damage Assessment for Small Crack Growth
Authors: Zhao Zhengwei Jack , Orisamolu Irewole Wally 
Published: November 2021

Abstract
Fatigue and fracture are typical random phenomena due to various uncertainty sources, including material property, initial flaw and crack shape, structural configuration and geometry around crack tip, load fluctuation, and other environmental factors. As contrast to the most commonly used probabilistic fatigue growth models, which are built based on simplified fatigue crack growth law, a framework of probabilistic fracture mechanics based fatigue damage assessment methodology for small crack propagation is presented here. The proposed modeling is developed based on a comprehensive fatigue crack growth model, which accounts the effect of crack aspect ratio, stress ratio, and crack closure and retardation. Due to the complicated nature of the fatigue damage modeling adopted, a high non-linear limit state function with discontinuity resulted from physical domain jumping and overlapping are encountered. The advanced fast probability integration techniques in conjunction with response surface methodology and Monte Carlo simulation are used and the accuracy of the analysis is verified. The interface between probabilistic analysis package and the deterministic fracture mechanics analysis program is developed for the purpose of uncertainty propagation. The probability of failure of fatigue damage is computed first. The statistical characteristics of estimated fatigue life and critical crack size are obtained and presented through CDF/PDF curves. The sensitivity analysis is also performed, which provides an indication of the order of importance for the random variables considered. The results of the study have shown robustness and efficiency of the probabilistic analysis to deal with the real world challenge of uncertainty modelling, propagation, and quantification. Currently, possibility to combine the subject probabilistic damage assessment methodology with reliability updating techniques is under the investigation. The successfulness of the presented research activity will address an important issue of quantitative risk analysis for aging structures subjected to accumulative material damage.
Analysis of the Stem-Sleeve Interface in a Modular Titanium Alloy Femoral Component for Total Hip Replacement
Authors: Kurtz S. M. , Srivastav S. , Dwyer K. , Ochoa J. , Brown S. 
Published: November 2021

Abstract
Modular femoral components for total hip arthroplasty have been clinically available since the 1980s. Despite the widespread use of interlocking tapers in hip prostheses, researchers have raised concerns about fretting, which has been clinically observed at the tapered modular interface of retrieved femoral heads and the trunions, as well as at the stem-sleeve junctions of retrieved femoral stems. Fretting can lead to degradation of the modular interfaces by the mechanisms of fretting wear, fretting corrosion, and fretting fatigue, all of which have potentially negative consequences for a total hip arthroplasty.
Near Net-Shape Fabrication of Hydroxyapatite and HA-Alloy Composites
Authors: Litsky Alan S. , Sandhage Ken H. , Saw Eadan , Briggs Susahn , Gallagher Patrick K. 
Published: November 2021

Abstract
Near net-shaped bodies of hydroxyapatite (HA), Ca10(PO4)6(OH)2, have been fabricated by the oxidation of solid, metal-bearing precursors. High-energy mechanical alloying was used to produce an intimate powder mixture of metallic calcium and calcium pyrophosphate, β-Ca2P2O7, (4:3 ratio) that possessed an overall stoichiometry consistent with HA. The milled Ca-Ca2P2O7 mixtures were sufficiently malleable to allow for compaction, pressing, and machining into shaped green bodies with relatively high densities (80–86%). The green bodies were converted into phase-pure HA through heat treatments at 500–600° C in dry oxygen (for Ca oxidation), 850° C in moist oxygen or air (for HA formation), and 1100–1150° C in moist oxygen or air (for sintering). The offsetting volume changes associated with calcium oxidation (Vm[CaO] &lt; Vm[Ca]) and subsequent HA formation (Vm[HA] &gt; 4Vm[CaO] + 3Vm[Ca2P2O7]) resulted in HA bodies that retained the shapes and dimensions of the metal-bearing precursors to within a few percent. Current work is focused on the formation of interpenetrating composites of HA and implant grade cobalt-chromium alloy by similar methods.
Failure of Ceramic Coatings on Soft Substrates
Authors: Lawn Brian R. 
Published: November 2021

Abstract
A design concept for potentially hard damage-resistant ceramic coatings on relatively soft substrates is proposed. Such coating structures are of direct relevance to biomechanical structures, especially teeth and dental crowns. In this study failure modes in bilayers and trilayers with relatively hard, brittle coating outerlayers on soft, tough substrate underlayers are evaluated. Coating/substrate systems of interest include ceramic/ceramic, ceramic/metal, and ceramic/polymer. A key element of these structures is a well-bonded interface, to prevent delamination during stressing. The objective is to arrest intrusive coating cracks in a tough sublayer, rather than merely to deflect them along a weak interface.
Clinical Performance: A Reflection of Damage Accumulation
Authors: Rekow E. Dianne , Thompson Van P. 
Published: November 2021

Abstract
Clinical performance of an prosthesis is directly dependent on damage introduced during fabrication and during fatigue loading associated with function. The relation between shaping damage and fatigue damage on clinical performance of all-ceramic dental crowns was investigated. Materials used commercially for all-ceramic crowns and investigated in this study included a series of different microstructures of machinable glass ceramics (Corning), aluminas and porcelains (Vita Zahnfabrik), and zirconias (Norton).
The Tooth as a Basis for Biomimetic Design
Authors: Thompson Van P. , Kao Stephen , Kirkpatrick Ivory 
Published: November 2021

Abstract
Teeth are uniquely capable of withstanding high forces (&gt;200 N) with small contact area (&lt; 0.5 mm2) and a high number of fatigue cycles (&gt; 107) with little evidence of damage. Yet the tooth is comprised of an outer very brittle, anisotropic, highly crystalline enamel layer supported by an inner soft, but tough dentin. These structures are joined by a small (appoximately 30 microns wide) transition zone called the dento-enamel junction (DEJ). The DEJ plays a critical role in transfer of stress across the layers of the tooth. How the enamel-dentin complex (EDC) comprised of these layers and the DEJ is able to withstand the high contact loads and high cycle fatigue is not well understood. An understanding of the interplay of the various components would serve as the basis for design of dental ceramic or resin based composite crowns capable of service lives approaching those on natural teeth. Current all ceramic crowns have high failure rates (1–5% per yr) on molar teeth and improved performance is required before CAD-CAM restorations can be successful.
Deformation and Failure in Stochastic Fibrous Networks: Scale, Dimension and Application
Authors: Sastry A. M. , Wang C. W. , Berhan L. 
Published: November 2021

Abstract
Simulating local deformation and failure in stochastic fibrous materials is of interest in a number of key materials technologies, including papers and filters, electrochemical substrates, and biomaterials. The local initiators of both deformation and damage are of key technological interest as they govern the properties of networks, and allow rational design of networks once variance in global properties is reasonable predicted.
Here, we examine several key microphenomena associated with failure of these networks, and further, map loading and environmental conditions under which each dominate. These mechanisms include tensile and bending failures, failures due to stress risers resulting from the way in which particles are bonded, and failures due to morphological changes (such as corrosion processes in batteries).
We also describe stochastic approaches for particle/fiber network generation, including the tracking of key geometric features. We show that single-parameter distribution functions rarely capture the real morphological variability seen in engineered microstructures, and suggest a methodology for more robust descriptions. We also present results of both large and small scale simulations of failure progression, and describe the importance of scale effect in numerical methods.
Advances in Probabilistic Methods
Authors: Cruse Thomas A. 
Published: November 2021

Abstract
Advances in probabilistic methods to support the design of mechanical systems is now moving to the engineering desktop. Basic modeling strategies are understood and in use in many applications. There are still issues to be resolved in the application of these methods to reliability critical applications. Some of these issues will be highlighted. At the same time, the design of complex aerospace systems requires more than just probabilistic methods as we know them now. The presentation will review a recent study by its author on the development and application of non-traditional and non-deterministic methods new methods to the life cycle design and analysis of extremely complex aerospace systems. Not only “traditional” mathematical analysis methodologies (such as mathematical optimization, Bayesian methods, or robust statistical design) are reviewed, but also “soft” or “non-traditional” methods (such as neural networks, fuzzy logic or genetic algorithms). In particular, emphasis will be given to the synthesis of many of these elements into the design systems of the future.
An Investigation of Fatigue in Polymer/Metal Composites
Authors: Kung E. , Mercer C. , Allameh S. , Popoola O. , Soboyejo W. O. 
Published: November 2021

Abstract
The fatigue behavior of Fe-Ni-base metal/polymer composites is discussed in this paper. These are proposed as self lubricating surfaces with the potential to replace conventionally lubricated pistons in automotive engines. Following a description of composite microstructure and basic mechanical properties, the paper examines the effects of polymer volume fraction on long fatigue crack growth. The effects of temperature on fatigue crack growth are then elucidated before presenting some initial fracture mechanics concepts for the prediction of fatigue life. The implications of the results are assessed for the design of durable surfaces.
Probabilistic Approaches to the Prediction of the Effects of Multiple Parameters on the Mechanical Properties of Gamma-Based Titanium Aluminides
Authors: Soboyejo A. B. O. , Ni Y. , Mercer C. , Soboyejo W. O. 
Published: November 2021

Abstract
Multiple parameter expressions of the form, Y = αoXiαi (where αo and ai are empirically-derived exponents), are presented for the prediction of the effects of multiple parameters, Xi, on the mechanical properties, Y, of gamma-based titanium aluminides. The multiparameter expressions, obtained via multiple linear regression techniques, provide single functions for the prediction of the combined effects of composition, microstructure and temperature on basic mechanical properties such as yield/ultimate tensile strength, plastic strain to failure and fracture toughness. Approximate exponential reliability functions are also presented for the prediction of the probabilities of failure/survival at various possible stress/strain/stress intensity factor levels. The use of Bayes theorem is proposed for the improvement of the exponential reliability functions as more data becomes available. Simplified analytical methods are presented for the prediction of the combined errors of prediction. The paper highlights the need for multiparameter probabilistic mechanics approaches to the prediction of basic mechanical properties.
30 Blood-based glycoprotein signatures in advanced non-small-cell lung carcinoma (NSCLC) receiving first-line immune checkpoint blockade
Authors: Lindpaintner Klaus , Cheng Michael , Prendergast Jillian , Normington Karl , Wong Maurice , Xu Gege , Cong Xini , Rice Rachel , Lawrence Marissa , Michael Kesi , Serie Daniel 
Published: November 2021

BackgroundImmune checkpoint blockade is an integral component of first-line therapy for most patients with ad-vanced non-small cell lung cancer (NSCLC), however individual patient outcomes are highly variable and improved biomarkers are needed. Protein glycosylation is an emerging mechanism of immune evasion in cancer. We examined blood-based glycopeptide signatures in a cohort of advanced NSCLC patients treated with first-line immune checkpoint blockade.MethodsPretreatment blood samples were obtained from 46 advanced NSCLC patients treated with first line pembrolizumab or pembrolizumab + carboplatin + pemetrexed. All patients provided written in-formed consent to the institutional review board–approved protocols (#02–180 and 13–367) at the Da-na-Farber/Harvard Cancer Center (Boston, MA), and the study was conducted in accordance with the Declaration of Helsinki. Samples were analyzed using an advanced glycoproteomics platform (Inter-Venn Biosciences) that combines ultra-high-performance liquid chromatography coupled to triple quadrupole mass spectrometry with a proprietary neural-network-based data processing engine. 409 individual glycopeptide (GP) signatures derived from 67 abundant serum proteins were analyzed and correlated with overall survival (OS) and other clinical outcomes.ResultsWe identified 30 GPs with abundance differences using a False Discovery Rate (FDR) threshold of 0.05. Using the 5 most predictive GP markers, we created a multivariable model for OS by generating leave-one-out cross-validation (LOOCV) scores and determining an optimized cutoff value of -0.83 (range: -2.2 - 3.4) for these scores using Harrell’s concordance index. The median overall survival was 2.8 years for patients (n=14) whose GP classifier value was above the cutoff and 0.8 years for patients (n=32) whose GP classifier value was below the cutoff (HR 7.4, 95% CI 1.7–32.1, p=0.007) The model’s perfor-mance was not affected by sex, age, or treatment regimen.ConclusionsBlood-based glycopeptide signatures may represent novel, non-invasive biomarkers of clinical out-come to first-line immune checkpoint blockade in advanced NSCLC. Additional research is needed to validate these findings in larger cohorts and to explore potential applications relevant to clinical decision-making.Ethics ApprovalThe study obtained ethics approval from the institutional review board (approved protocol #02–180 and 13–367) at the Dana-Farber/Harvard Cancer Center (Boston, MA), and the study was conducted in accordance with the Declaration of Helsinki.ConsentAll patients provided written informed consent to the institutional review board–approved protocols (#02–180 and 13–367) at the Dana-Farber/Harvard Cancer Center (Boston, MA), and the study was conducted in accordance with the Declaration of Helsinki.
53 Unique insights into PDAC development revealed by both InSituPlex® and imaging mass cytometry
Authors: Quong Andrew , Rees Mark , Maclean Kirsteen , Manesse Mael , Nieto Jordan , Esch Amanda , Fleury Devan , Wharton Keith , Chatterjee Gourab 
Published: November 2021

BackgroundPancreatic cancer remains a deadly disease due to difficulties hindering its early diagnosis, giving way to metastasis of the tumor and resulting in poor prognosis. While there are many neoplasms of the pancreas, pancreatic invasive ductal adenocarcinoma (PDAC) is the most common and treatment options are few, with poor overall survival. Aggressive surgeries such as the Whipple procedure coupled to systemic chemotherapy is one of the few treatment options. Recently, several publications have demonstrated improved outcomes with the inclusion of immunotherapy to cytotoxic drug combinations in some patients, however optimally selecting patients as candidates for immunotherapy-chemotherapy combinations remains a critical challenge. The complexities of the tumor microenvironment have been implicated in the failure of chemotherapy, radiation therapy, and immunotherapy. The tumor microenvironment of PDAC is especially rich with multiple interactions between pancreatic epithelial/cancer cells, stromal cells, immune cells and the extracellular matrix (ECM). PDACs are characterized by a complex ECM of desmoplastic reaction consisting of an extensive and dense fibrotic stroma that surrounds and infiltrates clusters of malignant epithelial cells, together with the loss of basement membrane integrity and an abnormal vasculature.MethodsIn the present study we demonstrate a tissue phenotyping workflow combining three complementary methods that can unravel novel insights in the complex tumor microenvironment. This novel translational workflow delivers tissue morphology information, spatial phenotyping of immune cell population on whole slides, and high dimensional imaging in selected regions of interest (ROI), by combining H&E, multiplex immunofluorescence (mIF), and Imaging Mass Cytometry (IMC™).ResultsThe use of the InSituPlex® UltiMapper® I/O PD-L1 kit enabled the streamlined combination and alignment of H&E and mIF data, leading to the strategic selection of relevant ROIs, while utility of IMC technology enabled downstream imaging of 35 protein markers associated with the ECM in the selected ROIs to provide a deeper understanding of the tumor microenvironment.ConclusionsThe incorporation of advanced multiplex imaging platforms such as mIF and IMC with routine H&E workflow in tumor biology can deliver some of the much-needed insight into tumor morphology, cellular composition, cellular functions, and cell-cell interactions and paves the way for potentially improved clinical prognosis and efficacy prediction in patients with cancer.
68 Rapid detection of somatic variants in human leukocyte antigen class 1 genes from solid tumor samples
Authors: Bharanikumar Ramit , Beutner Karl , Khan Aly , Perera Jason 
Published: November 2021

BackgroundHuman Leukocyte Antigens (HLA) class 1 proteins are important for recognizing tumor specific mutations (neoantigens) and presenting them to CD8+ T-cells. Somatic mutations in HLA genes can potentially reduce the set of neoantigens available for presentation to T-cells, providing a possible immune escape mechanism for tumors. The presence of mutations in HLA genes may thus affect an individual’s response to Immune Checkpoint Blockade therapy but calling somatic variants in HLA genes is challenging given high degrees of polymorphism and the presence of pseudogenes in HLA loci. Here, we present a rapid, modular algorithm to detect somatic variants in HLA class 1 genes from next-generation sequencing data.MethodsOur method takes as input matched tumor and normal sequencing (BAM) files and a patient‘s HLA type. Our first step involves mapping and aligning reads to the full-length HLA class 1 genes of an individual patient. Next, we filter reads to minimize sequencing errors and process them to account for potential cross-mapping between genes in the broader HLA locus. Our algorithm uses the final set of processed reads from matched tumor and normal sequencing files to call somatic variants. The final set of variants are then provided with a genetic variant annotation that summarizes their functional effect.ResultsWe validated the efficacy of our approach using TCGA samples that were previously known to contain somatic HLA mutations. Out of a total of 46 mutations previously characterized from 41 samples, our algorithm detected 43 mutations with the correct functional annotation and did so with a computational run-time that is an order of magnitude faster than the current gold-standard approach. Eight of these mutations were previously validated using PacBio long-read sequencing, and all of these validated mutations were detected by our method. Additionally, we analyzed transcriptomic data in samples containing nonsense mutations and detected a transcriptomic signature in RNA-seq data that corresponded to the Nonsense Mediated Decay pathway.ConclusionsOur findings show that our algorithm can reliably and rapidly detect somatic mutations in HLA class 1 classical genes. We leveraged multi-modal TCGA data and modules developed at Tempus to link samples with nonsense mutations to the nonsense mediated decay pathway. This allowed us to posit a possible biological mechanism that could result in increased resistance to immunotherapy because of somatic HLA mutations. Finally, we emphasize that our approach is modular and can be extended to call somatic variants in other non-classical and class 2 HLA genes.
73 Characterization of tumor-infiltrating T-cell repertoire in human cancers
Authors: Harding Taylor , Yang Qidi , Mineo Brittany , Malinauskas Jenna , Perera Jason , Beutner Karl , Lau Denise , Khan Aly 
Published: November 2021

BackgroundTCR and BCR repertoire profiling is a promising technique that can provide a clinically useful window into the complex interactions between tumor cells and infiltrating lymphocytes. Despite recent advances in repertoire sequencing methods, the characterization of tumor-infiltrating T-cell repertoires has been limited to small sample sizes due to technical and material constraints. In this study, we constructed a large multidimensional database of repertoire data covering a diverse landscape of HLA genotypes and tumor neoantigens from routine clinical sequencing. We present a descriptive summary of repertoire profiles derived from tens of thousands of tumor samples from over fifty different cancer cohorts and characterize the associations between T-cell repertoires and various clinical and molecular features.MethodsTo enrich immune receptor transcripts detected by the Tempus RNA-sequencing workflow, hybrid capture probes tiling TCR and BCR genes were used. Repertoire profiling reads were aligned, assembled, and annotated against IMGT reference sequences. Repertoires are profiled as a component of Tempus|xT RNA sequencing and are summarized here for >25 thousand tumor samples from over 50 different cancer cohorts.ResultsWe demonstrate that the use of TCR/BCR hybrid capture probes is an effective method for enriching immune receptor transcripts in RNA-sequencing data without interfering with downstream transcriptomic analysis. These repertoires were profiled as part of a larger, multimodal DNA/RNA-sequencing pipeline that quantifies a variety of tumor clinical and molecular features. We explored the correlation between high-level repertoire metrics like richness (the number of unique receptor clonotypes in a given repertoire) and clonality/evenness (Shannon entropy) against both gene expression-based metrics (i.e. immune cell infiltration estimates, etc.) and mutational patterns (mutational burden and neoantigen load). Finally, we observed that the repertoire clonality of B-cell and T-cell driven cancers frequently exhibits clear monoclonal dominance for the tumor cells’ lymphoid receptors.ConclusionsTCR/BCR repertoire profiling can be incorporated into high-volume clinical RNA sequencing to generate a diverse multimodal dataset for studying the tumor-immune microenvironment. By creating a large-scale database of TCR/BCR repertoire profiles from a variety of tissue, HLA genotypes, and mutational contexts, we can better resolve the molecular and clinical correlates of cancer with host adaptive immunity.