Dynamic Behavior Analysis of a Rotating Shaft with an Elliptical Breathing Surface Crack

Open access via the Springer Compact Acknowledgements The authors would like to thank the anonymous reviewers for their valuable suggestions that helped in improving the manuscript.Peer reviewedPublisher PD

The role of microalloying on tuning the mechanical performance of Cu-Zr based shape memory alloys

Shape Memory Alloys (SMAs) are an interesting class of materials that possess sensing and actuation functions due to Shape Memory Effect (SME). Although SME is observed in NiTi where high recoverable stress-strain is observed, there are limitations associated with implementation of NiTi such as high cost compared to cost-effective elements (i.e., Cu) and the inability to observe SME at temperatures above ~100oC. Therefore, a cost-effective and temperature-adaptive replacement (CuZr-based SMAs) may replace NiTi in sensing and actuation applications. The tribological performance of CuZr-based SMAs is investigated by wear and hardness tests at Room Temperature (RT) and high temperature. CuZr-based SMAs are obtained by rapid solidification and the microstructure is examined using X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). Due to poor SME of Cu50Zr50 at.% SMA compared to NiTi, a microalloying element (i.e., Co) is introduced in place of Cu at different at.% in order to promote martensitic transformation, leading to enhanced mechanical performance. This research found that microalloying with Co0.5 at.% at RT decreased mass loss by 46% compared to Cu50Zr50. However, when operating at 100oC, mass loss of the same alloy only decreased by 10%. Additionally, other microalloying elements such as Fe and Mn were investigated to improve the wear performance of CuZr-based SMAs, it was found that partial replacement of Cu by 0.5 at.% Fe, results in a lifetime enhancement of about 30.5% while for 0.5 at.% Mn the lifetime enhancement is about 21%. Microalloying is therefore an efficient strategy to develop CuZr-based SMAs as temperature adaptive shaft seals for engines. The synergistic effect of cooling rate control and concentration of microalloying element on mechanical performance of CuZr-based SMAs is also novel. In the case of fast cooling rate, 0.5 at.% Fe addition promotes formation of B19’ martensite upon wear testing, hence improving wear resistance. However, for slower cooling rate of the same alloy, relatively large volume fraction of B33 martensite is formed resulting in reduction of wear resistance

Automating drone image processing to map coral reef substrates using Google Earth Engine

While coral reef ecosystems hold immense biological, ecological, and economic value, frequent anthropogenic and environmental disturbances have caused these ecosystems to decline globally. Current coral reef monitoring methods include in situ surveys and analyzing remotely sensed data from satellites. However, in situ methods are often expensive and inconsistent in terms of time and space. High-resolution satellite imagery can also be expensive to acquire and subject to environmental conditions that conceal target features. High-resolution imagery gathered from remotely piloted aircraft systems (RPAS or drones) is an inexpensive alternative; however, processing drone imagery for analysis is time-consuming and complex. This study presents the first semi-automatic workflow for drone image processing with Google Earth Engine (GEE) and free and open source software (FOSS). With this workflow, we processed 230 drone images of Heron Reef, Australia and classified coral, sand, and rock/dead coral substrates with the Random Forest classifier. Our classification achieved an overall accuracy of 86% and mapped live coral cover with 92% accuracy. The presented methods enable efficient processing of drone imagery of any environment and can be useful when processing drone imagery for calibrating and validating satellite imagery

Isocyanurate transformation induced healing of isocyanurate–oxazolidone polymers

Isocyanurate–oxazolidone (ISOX) polymers have been reported as a novel, intrinsically self‐healable thermoset, and their healing mechanism under the effect of nucleophiles, such as tertiary amines and pyridines during polymerization, is thoroughly investigated in this study. This work provides evidence that the healing behavior of the polymers results part from the transformation of isocyanurate to oxazolidone on the fracture surfaces of the ISOX polymers at elevated temperatures. The isocyanurate transformation is characterized by chemical composition of the ISOX polymers before and after a predetermined healing procedure, through a combination characterization of Fourier transform infrared spectroscopy and carbon nuclear magnetic resonance spectroscopy. From the chemical composition of the ISOX polymers, an increased oxazolidone fraction is observed after the healing event, which verifies the hypothesized healing mechanism. By correlating the change in oxazolidone fraction in the polymers during the healing event, with the corresponding healing performance of the polymers, healing efficiencies of the polymers are shown to be inversely proportional to the ratio of oxazolidone to isocyanurate in the polymers. The transformation to oxazolidone is also shown to be dependent on two variables, nucleophilicity of the polymerization catalyst and duration of the postcure. The isocyanate and epoxide polymerization mechanism in the presence of nucleophiles is also investigated to explain the effect of the catalyst nucleophilicity on the chemical composition as well as the healing performance of the ISOX polymers. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 137, 48698.Isocyanurate‐to‐oxazolidone transformation within the polymers for healing.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/1/app48695-sup-0001-FigureS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/2/app48698_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/3/app48698.pd

The association between living conditions and health among Syrian refugee children in informal tented settlements in Lebanon

BACKGROUND: This cross-sectional study explores the relationship between housing, social wellbeing, access to services and health among a population of Syrian refugee children in Lebanon. METHODS: We surveyed 1902 Syrian refugee households living in informal tented settlements in Lebanon in 2017. Logistic regressions assessed relationships between housing problems, socioeconomic deprivation, social environment and health. RESULTS: Of the 8284 children in the study, 33.0% had at least one health problem. A considerable number of households (43.1%) had > 8 housing problems. Children in these households had higher odds to have three or more health problems compared to children in households with < 6 housing problems (adjusted odds ratio [AOR], 2.39; confidence interval [CI], 1.50-3.81). Nearly three-quarters (74.3%) of households were severely food insecure. Children in these households had higher odds to have one health problem than those in food secure households (AOR, 1.75; CI, 1.11-2.76). There was a significant positive association between households that reported being unhappy with their neighbourhood and the number of children with health problems in those households. CONCLUSIONS: This study highlights the association between the physical and social living conditions and refugee children's health. Without multidimensional interventions that consider improvements to living conditions, the health of young Syrian refugees will continue to worsen

Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically "learn" models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on the learned model be more accurate than the estimation we could have obtained by sampling many system executions within the same amount of time? In this work, we investigate existing algorithms for learning probabilistic models for model checking, propose an evolution-based approach for better controlling the degree of generalization and conduct an empirical study in order to answer the questions. One of our findings is that the effectiveness of learning may sometimes be limited.Comment: 15 pages, plus 2 reference pages, accepted by FASE 2017 in ETAP

Bovine neonate natural killer cells are fully functional and highly responsive to interleukin-15 and to NKp46 receptor stimulation

Natural killer (NK) cells are key components of the innate immune system with their killing and cytokine producing abilities. Bovine NK cells have been characterized as NKp46+/CD3− lymphocytes, but little is known about these cells in neonatal calves. As the newborn calf, with an insufficiently developed acquired immunity, has to employ the innate immune system, we wanted to investigate whether neonate NK cells had the same characteristics as cells from older calves. Freshly isolated neonate and calf NK cells presented the same resting CD2+/CD25low/CD8−/low phenotype. Neonates less than 8 days old had one third of the circulating NKp46+ cells of older calves, but the NK cells proliferated more actively in vitro in the presence of interleukin (IL)-2 or IL-15. Moreover, neonate NK cells were more cytotoxic both in an NKp46 mediated redirected lysis assay and in direct killing of a bovine cell line MDBK when cultured in the presence of IL-15. Neonate and calf NK cells cultured in the presence of IL-2 and then stimulated with IL-12 produced similar dose-dependent interferon (IFN)-γ amounts, while IL-15 cultured NK cells did not give such a response whatever the age. However, neonatal NK cells cultured in IL-15 and stimulated by IL-12 concomitantly with cross-linking of NKp46, produced 4 to 5 times more IFN-γ than calf NK cells. These data suggest that although present in lower number at birth, neonate NK cells are fully functional and are more responsive to IL-15 and activation through the NKp46 receptor than NK cells from older calves

Presión, temperatura y tiempo de procesamiento para mejorar la extracción de aceite de Camelina sativa mediante pretratamiento texturizado de descompresión instantánea controlada (DIC)

Instant Controlled Pressure Drop (DIC) was evaluated as a texturing pre-treatment for the extraction of Camelina sativa (L.) oil. DIC was coupled to Accelerated Solvent Extraction (ASE), Pressing and Dynamic Maceration (DM). DIC optimization was performed by studying the effects of pressure, temperature and processing time on oil yield. DIC + ASE obtained seed-oil yields of 615.9±0.5 against 555.5±0.5 g oil/kg-ddb for untextured seeds (RM). Via pressing, oil yields were 490.9±0.5 and 444.7±0.5 g oil/kg-ddb for textured and untextured seeds, respectively. Through coupling DIC (P: 0.63 MPa and t: 105 s) to the pressing extraction (60 s) of seeds along with 2h of DM of meals, it was possible to reach 605.8 g oil/kg ddb of oil yield. The same results were not obtained for RM seeds, where after 24 h of DM extraction, the oil yield was 554.7 g oil/kg ddb. DIC allowed for an increase in Camelina oil yields, reduced extraction time and valorized pressing meals.La tecnología de Descompresión Instantánea Controlada (DIC) fue evaluada como un pretratamiento para la extracción de aceite de Camelina sativa (L.). El pretratamiento DIC fue acoplado a la Extracción Acelerada de Disolventes (ASE), al Prensado y a la Maceración Dinámica (DM). La optimización de DIC fue llevada a cabo a través del estudio de los efectos de presión, temperatura y tiempo de proceso en el rendimiento del aceite. ASE + DIC permitió alcanzar rendimientos de 615,9±0,5 comparado con 555,5±0,5 g aceite/kg-ddb (base seca) en el caso de las semillas sin texturización (RM). En el caso del prensado, los rendimientos fueron de 490,9±0,5 y 444,7±0,5 g aceite/kg-ddb para las semillas con y sin texturización, respectivamente. Al acoplar el tratamiento DIC (P: 0.63 MPa y t: 105 s) + la extracción por prensado de las semillas (60 s) + 2h de DM de las harinas, fue posible alcanzar un rendimiento de 606,7 g aceite/ kg ddb. No así para las semillas sin tratamiento, en las que posterior a 24 h de extracción por DM, el rendimiento fue de 554,7 g oil/kg ddb. La texturización DIC permitió incrementar los rendimientos del aceite de Camelina, reducir los tiempos de extracción y valorizar las harinas del prensado

Integrated datasets of proteomic and metabolomic biomarkers to predict its impacts on comorbidities of type 2 diabetes mellitus

© 2020 Cheema et al. Objective: The objective of the current study is to accomplish a relative exploration of the biological roles of differentially dysregulated genes (DRGs) in type 2 diabetes mellitus (T2DM). The study aimed to determine the impact of these DRGs on the biological pathways and networks that are related to the associated disorders and complications in T2DM and to predict its role as prospective biomarkers. Methods: Datasets obtained from metabolomic and proteomic profiling were used for investigation of the differential expression of the genes. A subset of DRGs was integrated into IPA software to explore its biological pathways, related diseases, and their regulation in T2DM. Upon entry into the IPA, only 94 of the DRGs were recognizable, mapped, and matched within the database. Results: The study identified networks that explore the dysregulation of several functions; cell components such as degranulation of cells; molecular transport process and metabolism of cellular proteins; and inflammatory responses. Top disorders associated with DRGs in T2DM are related to organ injuries such as renal damage, connective tissue disorders, and acute inflammatory disorders. Upstream regulator analysis predicted the role of several transcription factors of interest, such as STAT3 and HIF alpha, as well as many kinases such as JAK kinases, which affects the gene expression of the dataset in T2DM. Interleukin 6 (IL6) is the top regulator of the DRGs, followed by leptin (LEP). Monitoring the dysregulation of the coupled expression of the following biomarkers (TNF, IL6, LEP, AGT, APOE, F2, SPP1, and INS) highlights that they could be used as potential prognostic biomarkers. Conclusion: The integration of data obtained by advanced metabolomic and proteomic technologies has made it probable to advantage in understanding the role of these biomarkers in the identification of significant biological processes, pathways, and regulators that are associated with T2DM and its comorbidities