Stress distribution during cold compression of a quartz aggregate using synchrotron X-ray diffraction: Observed yielding, damage, and grain crushing

We report new experimental results that quantify the stress distribution within a quartz aggregate during pore collapse and grain crushing. The samples were probed with synchrotron X-ray diffraction as they were compressed in a multianvil deformation apparatus at room temperature from low pressure (tens of megapascal) to pressures of a few gigapascal. In such a material, stress is likely to concentrate at grain-to-grain contacts and vanish where grains are bounded by open porosity. Therefore, internal stress is likely to vary significantly from point to point in such an aggregate, and hence, it is important to understand both the heterogeneity and anisotropy of such variation with respect to the externally applied stress. In our quartz aggregate (grain size of ~4 μm), the measured diffraction peaks broaden asymmetrically at low pressure (tens of megapascal), suggesting that open pores are still a dominant characteristic of grain boundaries. In contrast, a reference sample of novaculite (a highly dense quartz polycrystal, grain size of ~6–9 μm) showed virtually no peak broadening with increasing pressure. In the quartz aggregate, we observed significant deviation in the pressure-volume curves in the range of P = 400–600 MPa. We suggest that this marks the onset of grain crushing (generally denoted as P* in the rock mechanic literature), which is commonly reported to occur in sandstones at pressures of this order, in general agreement with a Hertzian analysis of fracturing at grain contacts

Perceptions and Challenges for Adoption of Generics and Biosimilars in Oncology

Cancer care is increasingly becoming challenging in low resource settings. With the improved availability and access of generic medicines and biosimilars, cost-effective and affordable treatment can be offered to cancer patients. However, generics and biosimilars continue to be plagued with negative perceptions that impact the adoption of these products. Lack of understanding and negative perceptions regarding the quality, safety, effectiveness, integrity and stability, formulations, manufacturing, and costs of generics and biosimilars are more common in the developing countries. Their equivalence to innovator counterparts is often doubted. Collaborative efforts for enhanced utilization of generics and biosimilars in oncology should be made by physicians, healthcare professionals, manufacturers and sponsors of these drugs, and national healthcare systems. Steps to improve access and utilization of these drugs include procurement of high-quality generics and biosimilars, formulary management, supply chain integrity, continued safety surveillance, and educational programs to improve knowledge mitigate fears in healthcare professionals and patients. Objective and standard frameworks should be developed and used to identify the perceptions and factors impacting the adoption of generics and biosimilars. Outcomes in hematological malignancies can be improved with the adoption of generics and biosimilars, in particular in low-income countries where access and affordability of chemotherapy is challenging

ILC3 function as a double-edged sword in inflammatory bowel diseases

Inflammatory bowel diseases (IBD), composed mainly of Crohn’s disease (CD) and ulcerative colitis (UC), are strongly implicated in the development of intestinal inflammation lesions. Its exact etiology and pathogenesis are still undetermined. Recently accumulating evidence supports that group 3 innate lymphoid cells (ILC3) are responsible for gastrointestinal mucosal homeostasis through moderate generation of IL-22, IL-17, and GM-CSF in the physiological state. ILC3 contribute to the progression and aggravation of IBD while both IL-22 and IL-17, along with IFN-γ, are overexpressed by the dysregulation of NCR− ILC3 or NCR+ ILC3 function and the bias of NCR+ ILC3 towards ILC1 as well as regulatory ILC dysfunction in the pathological state. Herein, we feature the group 3 innate lymphoid cells’ development, biological function, maintenance of gut homeostasis, mediation of IBD occurrence, and potential application to IBD therapy

Deep learning algorithms for structural condition identification with limited monitoring data

To obtain actual conditions of infrastructure assets and manage them more efficiently, extensive research efforts have beenplaced on structural health monitoring (SHM), especially those using data-driven methods. Recently, deep learning becomes a research hotspotin many application areas, including the SHM domain. Their performance largely relies on the quality and quantity of the training data, obtainedeither experimentally or numerically. Due to the time and expense restraints, field or laboratory test data are normally limited by the variationof structural conditions, while the quality of numerical simulation data is subjective to experts' modelling skills. Therefore, the actualperformance of deep learning algorithms with limited training data needs to be studied, and the alternative ways to generate more training dataneed to be developed. In this work, we develop a new one-Dimensional Convolutional Neural Network (1D-CNN) for structural conditionidentification. A laboratory case study is conducted to evaluate the performance of the algorithm. A steel Warren truss bridge structure is constructed and instrumented with accelerometers and impact hammer. The vibration tests under seven different scenarios are conducted, and each scenario has five repeated test data. The algorithm is trained with different quantities of training data (from one test data to four test data for each scenario). The results show that condition identification results become reliable with at least three repeated test data. To overcome the challenge of limited monitoring data, we propose the potential application of Generative Adversarial Networks (GANs) to generate morereliable training data

Stress Distribution During Cold Compression of Rocks and Mineral Aggregates Using Synchrotron-based X-Ray Diffraction

SUMMARY We report detailed procedures for compression experiments on rocks and mineral aggregates within a multi-anvil deformation apparatus coupled with synchrotron X-radiation. Such experiments allow quantification of the stress distribution within samples, that ultimately sheds light on compaction processes in geomaterials

Procalcitonin and Interleukin-10 May Assist in Early Prediction of Bacteraemia in Children With Cancer and Febrile Neutropenia

ObjectivesFebrile neutropenia (FN) causes treatment disruption and unplanned hospitalization in children with cancer. Serum biomarkers are infrequently used to stratify these patients into high or low risk for serious infection. This study investigated plasma abundance of cytokines in children with FN and their ability to predict bacteraemia.MethodsThirty-three plasma cytokines, C-reactive protein (CRP) and procalcitonin (PCT) were measured using ELISA assays in samples taken at FN presentation (n = 79) and within 8-24 h (Day 2; n = 31). Optimal thresholds for prediction of bacteraemia were identified and the predictive ability of biomarkers in addition to routinely available clinical variables was assessed.ResultsThe median age of included FN episodes was 6.0 years and eight (10%) had a bacteraemia. On presentation, elevated PCT, IL-10 and Mip1-beta were significantly associated with bacteraemia, while CRP, IL-6 and IL-8 were not. The combination of PCT (≥0.425 ng/ml) and IL-10 (≥4.37 pg/ml) had a sensitivity of 100% (95% CI 68.8-100%) and specificity of 89% (95% CI 80.0-95.0%) for prediction of bacteraemia, correctly identifying all eight bacteraemia episodes and classifying 16 FN episodes as high-risk. There was limited additive benefit of incorporating clinical variables to this model. On Day 2, there was an 11-fold increase in PCT in episodes with a bacteraemia which was significantly higher than that observed in the non-bacteraemia episodes.ConclusionElevated PCT and IL-10 accurately identified all bacteraemia episodes in our FN cohort and may enhance the early risk stratification process in this population. Prospective validation and implementation is required to determine the impact on health service utilisation

The Influence of Propagation Model and Sectorization over WCDMA Capacity

In this paper we use a dynamic model that we have developed for WCDMA capacity analysis using MATLAB and a GIS based planning tool, to estimate the capacity of a mobile system under different conditions like number of cells, propagation model, sectorization and handover margin