Recrystallization and Related Annealing Phenomena fulfils the information needs of materials scientists in both industry and academia. The subjects treated in the book are all active research areas, ...forming a major part of at least four regular international conference series. This new third edition ensures the reader has access to the latest findings, essential to those working at the forefront of research in universities and laboratories. For those in industry, the book highlights applications of the research and technologically important examples. In particular, the third edition builds on the significant progress made recently in the following key areas:. Deformed state, including deformation to very large strains. Characterisation of microstructures by electron backscatter diffraction (EBSD). Modelling and simulation of annealing. . Continuous recrystallization.
50% revised and up-to-date, the 3rd edition highlights the significant recent literature results in grain growth in non-crystallizing systems; 3D characterization techniques; Quantitative modeling techniques, with all-new appendices on Texture and Measurements Synthesized, detailed coverage from leading authors bridges the gap between theory and practice by examining the application of quantitative, physically based models to metal forming processes Critical level of synthesis and pedagogy with an authored rather than edited volume
The use of III-nitride-based light-emitting diodes (LEDs) is now widespread in applications such as indicator lamps, display panels, backlighting for liquid-crystal display TVs and computer screens, ...traffic lights, etc. To meet the huge market demand and lower the manufacturing cost, the LED industry is moving fast from 2 inch to 4 inch and recently to 6 inch wafer sizes. Although Al2O3 (sapphire) and SiC remain the dominant substrate materials for the epitaxy of nitride LEDs, the use of large Si substrates attracts great interest because Si wafers are readily available in large diameters at low cost. In addition, such wafers are compatible with existing processing lines for 6 inch and larger wafers commonly used in the electronics industry. During the last decade, much exciting progress has been achieved in improving the performance of GaN-on-Si devices. In this contribution, the status and prospects of III-nitride optoelectronics grown on Si substrates are reviewed. The issues involved in the growth of GaN-based LED structures on Si and possible solutions are outlined, together with a brief introduction to some novel in situ and ex situ monitoring/characterization tools, which are especially useful for the growth of GaN-on-Si structures.
Machine Learning Predicts Laboratory Earthquakes Rouet‐Leduc, Bertrand; Hulbert, Claudia; Lubbers, Nicholas ...
Geophysical research letters,
28 September 2017, Volume:
44, Issue:
18
Journal Article
Peer reviewed
Open access
We apply machine learning to data sets from shear laboratory experiments, with the goal of identifying hidden signals that precede earthquakes. Here we show that by listening to the acoustic signal ...emitted by a laboratory fault, machine learning can predict the time remaining before it fails with great accuracy. These predictions are based solely on the instantaneous physical characteristics of the acoustical signal and do not make use of its history. Surprisingly, machine learning identifies a signal emitted from the fault zone previously thought to be low‐amplitude noise that enables failure forecasting throughout the laboratory quake cycle. We infer that this signal originates from continuous grain motions of the fault gouge as the fault blocks displace. We posit that applying this approach to continuous seismic data may lead to significant advances in identifying currently unknown signals, in providing new insights into fault physics, and in placing bounds on fault failure times.
Plain Language Summary
Predicting the timing and magnitude of an earthquake is a fundamental goal of geoscientists. In a laboratory setting, we show we can predict “labquakes” by applying new developments in machine learning (ML), which exploits computer programs that expand and revise themselves based on new data. We use ML to identify telltale sounds—much like a squeaky door—that predict when a quake will occur. The experiment closely mimics Earth faulting, so the same approach may work in predicting timing, but not size, of an earthquake. This approach could be applied to predict avalanches, landslides, failure of machine parts, and more.
Key Points
Machine learning appears to discern the frictional state when applied to laboratory seismic data recorded during a shear experiment
Machine learning uses statistical characteristics of the recorded seismic signal to accurately predict slip failure time
We posit that similar machine learning approaches applied to geophysical data in Earth will provide insight in fault frictional processes
This book is the first practical guidance on how to address sexual violence, using a comprehensive institution-wide approach. The authors provide how-to level information on policy writing, ...responding to disclosures, developing comprehensive prevention and response education programmes, conducting trauma-informed investigations and sanctioning.
This work addresses a fundamental question: To what extent is graphene graphite? In particular does 2D graphene have many of the same 3D mechanical properties as graphite, such as the bulk modulus ...and elastic constant c33? We have obtained, for the first time, unambiguous Raman spectra from unsupported monolayer graphene under pressure. We have used these data to quantify the out-of-plane stiffness of monolayer graphene, which is hard to define due to its 2D nature. Our data indicate a first physically meaningful out-of-plane stiffness of monolayer graphene, and find it to be consistent with that of graphite. We also report a shift rate of the in-plane phonon frequency of unsupported monolayer graphene to be 5.4 cm−1 GPa−1, very close to that of graphite (4.7 cm−1 GPa−1), contrary to the previous value for supported graphene. Our results imply that monolayer graphene has similar in-plane and out-of-plane stiffnesses, and anharmonicities to graphite.
The area adjacent to the milking parlor, accessible for grazing by lactating dairy cows (i.e., the grazing platform GP), can be limited on fragmented pasture-based dairy farms. Such farms, with a ...moderate overall farm stocking rate, typically have a much higher stocking rate of dairy cows on the GP. This study quantified the effects of farm fragmentation on milk and herbage production and profitability in a whole-farm systems-scale study over 3 yr (2017–2019). Four systems, each with an overall farm stocking rate of 2.5 cows/ha but with different grazing platform stocking rates (GPSR), were examined. The proportions of the overall farm area within the GP were 100%, 83%, 71%, and 63% in each of the 4 systems, respectively. Hence, the 4 systems had a GPSR of 2.5, 3.0, 3.5, and 4.0 cows/ha. The GP was used for grazing and silage (ensiled herbage) production, and the non-GP portion of each GPSR system was used solely for silage production. Concentrate supplementation per cow was the same across all GPSR systems; approximately 10% of the annual feed budget. All systems were compact spring-calving with 24 cows per system. We discovered a lower proportion of grazed herbage in the diet with higher GPSR. All silage produced on the non-GP areas was required to support higher GPSR on each of the systems. Annual herbage production and milk production per cow were not different between GPSR systems, resulting in similar milk production per hectare of the overall system area. The economic implications of different GPSR on fragmented farms were modeled in 2 scenarios: (1) quantifying the cost associated with different levels of farm area fragmentation; (2) investigating the optimum GPSR on fragmented pasture-based dairy farms, depending on variable criteria. A greater level of farm fragmentation lowered the profitability of pasture-based dairy production. Costs of production increased with higher GPSR and longer distances between GP and non-GP areas. At a fixed GP area, it was most profitable to increase GPSR up to 4 cows/ha on the GP when milk price was high, land rental price was low, and shorter distance existed between GP and non-GP areas.
The application of automated Electron Backscatter Diffraction (EBSD) in the scanning electron microscope, to the quantitative analysis of grain and subgrain structures is discussed and compared with ...conventional methods of quantitative metallography. It is shown that the technique has reached a state of maturity such that linescans and maps can routinely be obtained and analysed using commercially available equipment and that EBSD in a Field Emission SEM (FEGSEM) allows quantitative analysis of grain/subgrains as small as similar to0.2/ mu m. EBSD can often give more accurate measurements of grain and subgrain size than conventional imaging methods, often in comparable times. Subgrain/cell measurements may be made more easily than in the TEM although the limited angular resolution of EBSD may be problematic in some cases. Additional information available from EBSD and not from conventional microscopy, gives a new dimension to quantitative metallography. Texture and its correlation with grain or subgrain size, shape and position are readily measured. Boundary misorientations, which are readily obtainable from EBSD, enable the distribution of boundary types to be determined and CSL boundaries can be identified and measured. The spatial distribution of Stored Energy in a sample and the amount of Recrystallization may also be measured by EBSD methods. copyright 2001 Kluwer Academic Publishers.
The miR-17-92 cluster of microRNAs is elevated in colorectal cancer, and has a causative role in cancer development. Of the six miR-17-92 cluster members, miR-19a and b in particular are key ...promoters of cancer development and cell proliferation, while preliminary evidence suggests that miR-18a may act in opposition to other cluster members to decrease cell proliferation. It was hypothesised that miR-18a may have a homeostatic function in helping to contain the oncogenic effect of the entire miR-17-92 cluster, and that elevated miR-17-92 cluster activity without a corresponding increase in miR-18a may promote colorectal tumour progression. In colorectal cancer samples and corresponding normal colorectal mucosa, miR-18a displayed lower overall expression than other miR-17-92 cluster members. miR-18a was shown to have an opposing role to other miR-17-92 cluster members, in particular the key oncogenic miRNAs, miR-19a and b. Transfection of HCT116 and LIM1215 colorectal cancer cell lines with miR-18a mimics decreased proliferation, while a miR-18a inhibitor increased proliferation. miR-18a was also responsible for decreasing cell migration, altering cell morphology, inducing G1/S phase cell cycle arrest, increasing apoptosis, and enhancing the action of a pro-apoptotic agent. CDC42, a mediator of the PI3K pathway, was identified as a novel miR-18a target. Overexpression of miR-18a reduced CDC42 expression, and a luciferase assay confirmed that miR-18a directly targets the 3'UTR of CDC42. miR-18a mimics had a similar effect on proliferation as a small molecule inhibitor of CDC42. Inhibition of CDC42 expression is likely to be a key mechanism by which miR-18a impairs cancer cell growth, with a target protector experiment revealing miR-18a influences proliferation via direct inhibition of CDC42. Inhibition of CCND1 by miR-18a may also assist in this growth-suppression effect. The homeostatic function of miR-18a within the miR-17-92 cluster in colorectal cancer cells may be achieved through suppression of CDC42 and the PI3K pathway.
Narcolepsie Humphreys, Christopher J; Liu, Ran R; Simms, Taryn M
Canadian Medical Association journal (CMAJ),
04/2024, Volume:
196, Issue:
15
Journal Article
As a plant group, forage legumes present some unique advantages and disadvantages for ruminant production. When compared to grasses or cereals their main advantages are generally (i) low reliance on ...fertilizer nitrogen (N) inputs, (ii) high voluntary intake and animal production when feed supply is non-limiting and (iii) high protein content. The main disadvantages of forage legumes are generally (i) lower persistence than grass under grazing, (ii) high risk of livestock bloat and (iii) difficulty to conserve as silage or hay. In comparison to grass or legume monocultures, grass + legume mixtures have particular advantages such as more balanced feeding values, increased resource use efficiency and increased herbage production. However, maintaining the optimum legume contents (40-60% of herbage dry matter) to achieve these benefits remains a major challenge on farms. When compared to ruminant systems based on grass or cereals supplemented with fertilizer N, forage legume based ruminant systems tend to have less negative environmental impact on biodiversity, N losses to water and greenhouse gas emissions. Economically, the primary advantage of forage legumes over other forages is their ability to reduce fertilizer N costs and their main disadvantage is usually lower intensity of animal production per ha of land. Despite the numerous benefits of forage legumes for ruminant farming (to the farmer and wider society), their use is reported as being low or declining relative to other forages in many regions. This is most likely a result of their disadvantages being perceived to outweigh their advantages at farm level. This may change if the price ratio of fertilizer N to product (meat/milk) continues to increase as it has done in some regions in recent years.