Influence of Second-Order Effects on Thermoelastic Behaviour in the Proximity of Crack Tips on Titanium

The Stress Intensity Factor (SIF) is used to describe the stress state and the mechanical behaviour of a material in the presence of cracks. SIF can be experimentally assessed using contactless techniques such as Thermoelastic Stress Analysis (TSA). The classic TSA theory concerns the relationship between temperature and stress variations and was successfully applied to fracture mechanics for SIF evaluation and crack tip location. This theory is no longer valid for some materials, such as titanium and aluminium, where the temperature variations also depend on the mean stress. The objective of this work was to present a new thermoelastic equation that includes the mean stress dependence to investigate the thermoelastic effect in the proximity of crack tips on titanium. Westergaard’s equations and Williams’s series expansion were employed in order to express the thermoelastic signal, including the second-order effect. Tests have been carried out to investigate the differences in SIF evaluation between the proposed approach and the classical one. A first qualitative evaluation of the importance of considering second-order effects in the thermoelastic signal in proximity of the crack tip in two loading conditions at two different loading ratios, R = 0.1 and R = 0.5, consisted of comparing the experimental signal and synthetic TSA maps. Moreover, the SIF, evaluated with the proposed and classical approaches, was compared with values from the ASTM standard formulas. The new formulation demonstrates its improved capability for describing the stress distribution in the proximity of the crack tip. The effect of the correction cannot be neglected in either Williams’s or Westergaard’s model

A Systems Engineering Framework for Design, Construction and Operation of the Next Generation Nuclear Plant

Not since the International Space Station has a project of such wide participation been proposed for the United States. Ten countries, the European Union, universities, Department of Energy (DOE) laboratories, and industry will participate in the research and development, design, construction and/or operation of the fourth generation of nuclear power plants with a demonstration reactor to be built at a DOE site and operational by the middle of the next decade. This reactor will be like no other. The Next Generation Nuclear Plant (NGNP) will be passively safe, economical, highly efficient, modular, proliferation resistant, and sustainable. In addition to electrical generation, the NGNP will demonstrate efficient and cost effective generation of hydrogen to support the President’s Hydrogen Initiative. To effectively manage this multi-organizational and technologically complex project, systems engineering techniques and processes will be used extensively to ensure delivery of the final product. The technological and organizational challenges are complex. Research and development activities are required, material standards require development, hydrogen production, storage and infrastructure requirements are not well developed, and the Nuclear Regulatory Commission may further define risk-informed/performance-based approach to licensing. Detailed design and development will be challenged by the vast cultural and institutional differences across the participants. Systems engineering processes must bring the technological and organizational complexity together to ensure successful product delivery. This paper will define the framework for application of systems engineering to this $1.5B -$1.9B project

Denominators of Eisenstein cohomology classes for GL_2 over imaginary quadratic fields

We study the arithmetic of Eisenstein cohomology classes (in the sense of G. Harder) for symmetric spaces associated to GL_2 over imaginary quadratic fields. We prove in many cases a lower bound on their denominator in terms of a special L-value of a Hecke character providing evidence for a conjecture of Harder that the denominator is given by this L-value. We also prove under some additional assumptions that the restriction of the classes to the boundary of the Borel-Serre compactification of the spaces is integral. Such classes are interesting for their use in congruences with cuspidal classes to prove connections between the special L-value and the size of the Selmer group of the Hecke character.Comment: 37 pages; strengthened integrality result (Proposition 16), corrected statement of Theorem 3, and revised introductio

Three-dimensional Magnetic Resonance Imaging–based Printed Models of Prostate Anatomy and Targeted Biopsy-proven Index Tumor to Facilitate Patient-tailored Radical Prostatectomy—A Feasibility Study

In this prospective single-center feasibility study, we demonstrate that the use of three-dimensional (3D)-printed prostate models support nerve-sparing radical prostatectomy (RP) and intraoperative frozen sectioning (IFS) in ten men suffering from intermediate- and high-risk prostate cancer (PC), of whom seven harbored pT3 disease. Patient-specific 3D resin models were printed based on preoperative multiparametric magnetic resonance imaging (mpMRI) to provide an exact 3D impression of significant tumor lesions. RP and IFS were planned in a patient-tailored fashion. The 36-region Prostate Imaging Reporting and Data System (PI-RADS) v2.0 scheme was used to compare the MRI/3D print with whole-mount histopathology. In all cases, localization of the index lesion was correctly displayed by MRI and the 3D model. Localization of significant PC lesions correlated significantly (Pearson`s correlation coefficient of 0.88; p <  0.001). In addition, a significant correlation of the width, length, and volume of the tumor and prostate gland, derived from the printed model and histopathology, was found, using Pearson's correlation analyses and Bland-Altman plots. In conclusion, 3D-printed prostate models correlate well with final pathology and can be used to tailor RP. PATIENT SUMMARY: The use of three-dimensional (3D)-printed prostate models based on preoperative magnetic resonance imaging (MRI) may improve prostatectomy outcome. This study confirmed the accuracy of 3D-printed prostates compared with pathology from radical prostatectomy specimens. Thus, MRI-derived 3D-printed prostate models can assist in prostate cancer surgery

A neural basis for contagious yawning

Contagious yawning, in which yawning is triggered involuntarily when we observe another person yawn, is a common form of echophenomena—the automatic imitation of another’s words (echolalia) or actions (echopraxia) [1]. The neural basis for echophenomena is unknown; however, it has been proposed that it is linked to disinhibition of the human mirror-neuron system [1–4 ] and hyper-excitability of cortical motor areas [ 1 ]. We investigated the neural basis for contagious yawning using transcranial magnetic stimulation (TMS). Thirty-six adults viewed video clips that showed another individual yawning and, in separate blocks, were instructed to either resist yawning or allow themselves to yawn. Participants were videoed throughout and their yawns or stifled yawns were counted. We used TMS to quantify motor cortical excitability and physiological inhibition for each participant, and these measures were then used to predict the propensity for contagious yawning across participants. We demonstrate that instructions to resist yawning increase the urge to yawn and alter how yawns are expressed (i.e., full versus stifled yawns) but do not alter the individual propensity for contagious yawning. By contrast, TMS measures of cortical excitability and physiological inhibition were significant predictors of contagious yawning and accounted for approximately 50% of the variability in contagious yawning. These data demonstrate that individual variability in the propensity for contagious yawning is determined by cortical excitability and physiological inhibition in the primary motor cortex

SP701-A-Growing and Harvesting Switchgrass for Ethanol Production in Tennessee

Switchgrass is a warm-season perennial grass native to North America. The plant can reach heights up to 10 feet with an extensive root system. Once established, switchgrass well-managed for biomass should have a productive life of 10-20 years. Within the stand, switchgrass is an extremely strong competitor. However, it is not considered an invasive plant. Switchgrass adapts well to a variety of soil and climatic conditions. It is most productive on moderately well to well-drained soils of medium fertility and a soil pH at 5.0 or above. The high cellulosic content of switchgrass makes it a favorable feedstock for ethanol production. It is anticipated that switchgrass can yield sufficient biomass to produce approximately 500 gallons of ethanol per acre. While the Tennessee Biofuels Initiative includes a demonstration plant to make ethanol from switchgrass, the market for switchgrass as an energy crop remains limited. Producers will likely need to be located within 30 to 50 miles of a cellulosic ethanol plant. Producing switchgrass for energy generally occurs under some form of contractual arrangement with the end-user. To reap potential benefits from using switchgrass for cellulosic ethanol production, the system of production must be profitable for farmers and energy producers, as well as cost effective for consumers

SPA: Economical and workload-driven indexing for data analytics in the cloud

Selective queries are not uncommon in large-scale data analytics, for example, when drilling down into a specific customer in a dashboard. Traditionally, selective queries are accelerated by creating secondary indexes. However, because of their large size, expensive maintenance, and difficulty to tune and automate, indexes are typically not used in modern cloud data warehouses or data lakes. Instead, such systems rely mostly on full table scans and lightweight optimizations like min/max filtering, whose effectiveness depends heavily on the data layout and value distributions.We propose SPA as the vision for automatically optimizing selective queries for immutable copy-on-write data formats. SPA adaptively indexes subsets of the data in an incremental and workload-driven manner. It makes fine-grained decisions and continuously monitors their benefit, dynamically allocating an optimization budget in a way that bounds the additional cost of indexing. Furthermore, it guarantees a performance improvement in the cases where indexes - potentially partial ones - prove to be beneficial. When indexes lose their benefit due to a shifting workload, they are gradually deconstructed in favor of optimizations that accommodate recent trends. As SPA does not require information about updates performed on the data, it can also be employed as an accelerator for systems that do not control the data, e.g., in cloud data lakes