Ultrasonic Attenuation Measurements in Jet-Engine Titanium Alloys

In the inspection of titanium material intended for use in aircraft engines, a number of unusual phenomena are observed, including significant fluctuations of the amplitude and phase of back-surface echoes and of the amplitudes of pulse-echo signals from nominally identical flaws[1]. Practical implications include a broadening of the probability of detection curves and difficulties in determining the ultrasonic attenuation, a parameter used in interpreting flaw response data. Incorrect determination of attenuation can lead to errors in distance-gain corrections and hence in estimates of the magnitude of the flaw response. In this paper, we report experiments designed to elucidate the mechanisms responsible for these signal fluctuations

The Statistical Distribution of Grain Noise in Ultrasonic Images

Ultrasonic imaging technologies are rapidly being transitioned to the production environment. An example of this is occurring in the aerospace industry, where digital data acquisition and imaging are being used to improve the ultrasonic inspection of large grained alloys. [1] The availability of digital data and ever increasing computing power opens the door for more sophisticated data analysis techniques than have been used in the past. Such potential techniques include the Wiener filter to improve resolution, dynamic thresholding to improve detection, signal-to-noise (SNR) based material acceptance criteria, and the estimation of the probability of detection (POD) of a given inspection. [2–5] An element critical to the success of all these techniques is an accurate estimate the distribution of the ultrasonic reflections from grain boundaries which are commonly referred to as grain noise. This paper presents a technique to estimate the parameters of closed-form statistical distributions from grain noise data and analyzes the quality of the fit of several distributions to the grain noise found in ultrasonic images of titanium alloys

Observation and Interpretation of Microstructurally Induced Fluctuations of Back-Surface Signals and Ultrasonic Attenuation in Titanium Alloys

During ultrasonic inspection for flaws in engineering materials, it is important to understand the interactions between the inspecting beam and the microstructure in which flaws are embedded. It has been found that in certain materials such interactions can have dramatic effects on the characteristics of the beam as it propagates to and from a flaw and consequently can have deleterious effects on both flaw characterization and the probability of detection. It is well known that, the microstructure can backscatter energy, creating noise which can mask small flaws. In addition, a flaw signal can be attenuated by the removal of energy from the beam by absorption and scattering. Considerable progress has been made towards developing a theoretical understanding of these phenomena. For example, backscattered grain noise has been successfully modeled by Han and Thompson [1] for duplex microstructures that commonly occur in Ti-17 and Ti-6A1-4V alloys used in the rotating components of aircraft engines. In addition, attenuation has been modeled for randomly oriented, equiaxed, cubic microstructures [2], for textured, equiaxed, cubic, stainless-steel [3], and also for elongated textured microstructures [4]

Deep dyslexia and right hemisphere reading - A regional cerebral blood flow study

Deep dyslexia is an acquired reading disorder that is characterized by the production of semantic reading errors, greater success when reading aloud concrete and highly imageable words, frequent visual and visual-semantic errors, morphological errors and very poor reading of nonwords. The right hemisphere hypothesis proposes that in deep dyslexia the patient is not reading with an impaired version of the normal left hemisphere reading system, and cannot use that system for reading at all. Instead, a different reading system, located in the right hemisphere is used. The right hemisphere hypothesis was examined in this study by investigating the amount of cortical activation in the left and right cerebral hemispheres of a deep dyslexic patient (L.H.) during visual word recognition. Three experimental tasks were devised to isolate a Visual Word Recognition process and a Spoken Word Production process and these tasks were administered to the deep dyslexic patient as well as another patient with left-hemisphere-damage but a different form of acquired dyslexia (surface dyslexia) and two matched control subjects. Regional cerebral blood flow (rCBF) was monitored during performance on each of the tasks. For L.H., but not the other three subjects, rCBF in the right hemisphere was greater than in the left hemisphere during Visual Word Recognition. By contrast, there was greater activation of the left hemisphere than the right hemisphere for L.H. during Spoken Word Production; this was also true of the other three subjects, but the effect was statistically significant only for L.H. These results support the right-hemisphere hypothesis of deep dyslexia.link_to_subscribed_fulltex

Leukocyte telomere length in relation to pancreatic cancer risk: a prospective study.

BACKGROUND: Several studies have examined leukocyte telomere length (LTL) as a possible predictor for cancer at various organ sites. The hypothesis originally motivating many of these studies was that shorter telomeres would be associated with an increase in cancer risk; the results of epidemiologic studies have been inconsistent, however, and suggested positive, negative, or null associations. Two studies have addressed the association of LTL in relation to pancreatic cancer risk and the results are contrasting. METHODS: We measured LTL in a prospective study of 331 pancreatic cancer cases and 331 controls in the context of the European Prospective Investigation into Cancer and Nutrition (EPIC). RESULTS: We observed that the mean LTL was higher in cases (0.59 ± 0.20) than in controls (0.57 ± 0.17), although this difference was not statistically significant (P = 0.07), and a basic logistic regression model showed no association of LTL with pancreas cancer risk. When adjusting for levels of HbA1c and C-peptide, however, there was a weakly positive association between longer LTL and pancreatic cancer risk [OR, 1.13; 95% confidence interval (CI), 1.01-1.27]. Additional analyses by cubic spline regression suggested a possible nonlinear relationship between LTL and pancreatic cancer risk (P = 0.022), with a statistically nonsignificant increase in risk at very low LTL, as well as a significant increase at high LTL. CONCLUSION: Taken together, the results from our study do not support LTL as a uniform and strong predictor of pancreatic cancer. IMPACT: The results of this article can provide insights into telomere dynamics and highlight the complex relationship between LTL and pancreatic cancer risk

Diabetes mellitus, glycated haemoglobin and C-peptide levels in relation to pancreatic cancer risk: a study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

AIMS/HYPOTHESIS: There has been long-standing debate about whether diabetes is a causal risk factor for pancreatic cancer or a consequence of tumour development. Prospective epidemiological studies have shown variable relationships between pancreatic cancer risk and blood markers of glucose and insulin metabolism, overall and as a function of lag times between marker measurements (blood donation) and date of tumour diagnosis. METHODS: Pre-diagnostic levels of HbA(1c) and C-peptide were measured for 466 participants with pancreatic cancer and 466 individually matched controls within the European Prospective Investigation into Cancer and Nutrition. Conditional logistic regression models were used to estimate ORs for pancreatic cancer. RESULTS: Pancreatic cancer risk gradually increased with increasing pre-diagnostic HbA(1c) levels up to an OR of 2.42 (95% CI 1.33, 4.39 highest [≥ 6.5%, 48 mmol/mol] vs lowest [≤ 5.4%, 36 mmol/mol] category), even for individuals with HbA(1c) levels within the non-diabetic range. C-peptide levels showed no significant relationship with pancreatic cancer risk, irrespective of fasting status. Analyses showed no clear trends towards increasing hyperglycaemia (as marked by HbA(1c) levels) or reduced pancreatic beta cell responsiveness (as marked by C-peptide levels) with decreasing time intervals from blood donation to cancer diagnosis. CONCLUSIONS/INTERPRETATION: Our data on HbA(1c) show that individuals who develop exocrine pancreatic cancer tend to have moderate increases in HbA(1c) levels, relatively independently of obesity and insulin resistance-the classic and major risk factors for type 2 diabetes. While there is no strong difference by lag time, more data are needed on this in order to reach a firm conclusion