Ionization dynamics of iron plumes generated by laser ablation versus a laser‐ablation‐assisted‐plasma discharge ion source

The ionization dynamics (iron ion and neutral atom absolute line densities) produced in the KrF excimer laser ablation of iron and a laser‐ablation‐assisted plasma discharge (LAAPD) ion source have been characterized by a new dye‐laser‐based resonant ultraviolet interferometry diagnostic. The ablated material is produced by focusing a KrF excimer laser (248 nm,<1 J, 40 ns) onto a solid iron target. The LAAPD ion source configuration employs an annular electrode in front of the grounded target. Simultaneous to the excimer laser striking the target, a three‐element, inductor–capacitor, pulse‐forming network is discharged across the electrode–target gap. Peak discharge parameters of 3600 V and 680 A yield a peak discharge power of 1.3 MW through the laser ablation plume. Iron neutral atom line densities are measured by tuning the dye laser near the 271.903 nm (a 5D–y 5P0) ground‐state and 273.358 nm (a 5F–w 5D0) excited‐state transitions while iron singly ionized line densities are measured using the 263.105 nm (a 6D–z 6D0) and 273.955 nm (a 4D–z 4D0) excited‐state transitions. The line density, expansion velocity, temperature, and number of each species have been characterized as a function of time for laser ablation and the LAAPD. Data analysis assuming a Boltzmann distribution yields the ionization ratio (ni/nn) and indicates that the laser ablation plume is substantially ionized. With application of the discharge, neutral iron atoms are depleted from the plume, while iron ions are created, resulting in a factor of ∼5 increase in the plume ionization ratio. Species temperatures range from 0.5 to 1.0 eV while ion line densities in excess of 1×1015 cm−2 have been measured, implying peak ion densities of ∼1×1015 cm−3. © 1996 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70077/2/JAPIAU-79-5-2287-1.pd

Effects of laser‐ablation target damage on particulate production investigated by laser scattering with deposited thin film and target analysis

Experiments have been carried out to correlate ablated particulate density and size to the number of KrF excimer laser (248 nm, 40 ns, <1.2 J) pulses incident on a single location of a pure solid aluminum target and to relate particulate production to target surface damage. An analysis of laser ablation deposited aluminum films on silicon substrates was used to determine the density of ablated particulate greater than 0.5 μm in diameter. For an undamaged target, the laser deposited particulate density was on the order of 8.6×105 cm−2 per 1000 shots. A damaged target (following 1000 laser pulses) produced a density on the order of 1.6×106 cm−2 per 1000 shots on the substrate. Dye laser optical scattering was also used to measure, in real time, the velocity of the particulate and the relative particulate density in the laser‐ablation plume versus target damage. Results indicated a rapid rise in the production of particulate as target damage was increased up to 3000 laser pulses; after this number of shots the density of particulate in the laser ablation plume saturated. A peak in the scattered light for each stage of target damage occurred 40 μs after the initial KrF laser pulse, translating to a velocity of about 100 m/s for the smaller particulate (<1 μm diameter). The later scattered signal, around 160 μs, was apparently due to the larger particulate (5–15 μm), traveling at a velocity of approximately 25 m/s. Particulate production is related to the formation of laser ablation‐induced cones on the damaged targets. © 1996 American Institute of Physics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70140/2/APPLAB-68-23-3245-1.pd

Estrogen-related and other disease diagnoses preceding Parkinson’s disease

PURPOSE: Estrogen exposure has been associated with the occurrence of Parkinson's disease (PD), as well as many other disorders, and yet the mechanisms underlying these relations are often unknown. While it is likely that estrogen exposure modifies the risk of various diseases through many different mechanisms, some estrogen-related disease processes might work in similar manners and result in association between the diseases. Indeed, the association between diseases need not be due only to estrogen-related factors, but due to similar disease processes from a variety of mechanisms. PATIENTS AND METHODS: All female Parkinson's disease cases between 1982 and 2007 (n = 12,093) were identified from the Danish National Registry of Patients, along with 10 controls matched by years of birth and enrollment. Conditional logistic regressions (CLR) were used to calculate risk of PD after diagnosis of the estrogen-related diseases, endometriosis and osteoporosis, conditioning on years of birth and enrollment. To identify novel associations between PD and any other preceding conditions, CLR was also used to calculate the odds ratios (ORs) for risk of PD for 202 different categories of preceding disease diagnoses. Empirical Bayes methods were used to identify the robust associations from the over 200 associations produced by this analysis. RESULTS: We found a positive association between osteoporosis and osteoporotic fractures and PD (OR = 1.18, 95% confidence interval [CI] of 1.08–1.28), while a lack of association was observed between endometriosis and PD (OR = 1.37, 95% CI 0.99–1.90). Using empirical Bayes analyses, 24 additional categories of diseases, likely unrelated to estrogen exposure, were also identified as potentially associated with PD. CONCLUSION: We identified several novel associations, which may provide insight into common causal mechanisms between the diseases or greater understanding of potential early preclinical signs of PD. In particular, the associations with several categories of mental disorders suggest that these may be early warning signs of PD onset or these diseases (or the causes of these diseases) may predispose to PD.US Public Health Service (R01 NS36711-09); Robert P. and Judith N. Goldberg Foundation; Aarhus University Hospital Department of Clinical Epidemiology's Research Foundatio

Tailoring Capture-Recapture Methods to Estimate Registry-Based Case Counts Based on Error-Prone Diagnostic Signals

Surveillance research is of great importance for effective and efficient epidemiological monitoring of case counts and disease prevalence. Taking specific motivation from ongoing efforts to identify recurrent cases based on the Georgia Cancer Registry, we extend recently proposed "anchor stream" sampling design and estimation methodology. Our approach offers a more efficient and defensible alternative to traditional capture-recapture (CRC) methods by leveraging a relatively small random sample of participants whose recurrence status is obtained through a principled application of medical records abstraction. This sample is combined with one or more existing signaling data streams, which may yield data based on arbitrarily non-representative subsets of the full registry population. The key extension developed here accounts for the common problem of false positive or negative diagnostic signals from the existing data stream(s). In particular, we show that the design only requires documentation of positive signals in these non-anchor surveillance streams, and permits valid estimation of the true case count based on an estimable positive predictive value (PPV) parameter. We borrow ideas from the multiple imputation paradigm to provide accompanying standard errors, and develop an adapted Bayesian credible interval approach that yields favorable frequentist coverage properties. We demonstrate the benefits of the proposed methods through simulation studies, and provide a data example targeting estimation of the breast cancer recurrence case count among Metro Atlanta area patients from the Georgia Cancer Registry-based Cancer Recurrence Information and Surveillance Program (CRISP) database

Characterization of a laser-ablation-assisted-plasma-discharge-metallic ion source

Experiments have been carried out to characterize further the properties of a new laser-ablation-assisted-plasma-discharge source of metallic aluminium ions. Laser ablation is accomplished by focusing a KrF excimer laser (<1.2 J, 40 ns, 248 nm) onto a solid aluminium target with a fluence of approximately 10 J cm-2. Through gated optical emission spectroscopy, the laser ablation plume optical emission is observed to contain only aluminium neutral atom transitions after approximately 100 ns. With the application of a 3.6 kV, 760 A discharge, the neutral atom plume is transformed into a plasma with the emission dominated by Al+ and Al2+ ion transitions. Through time-resolved spectroscopy, emission intensity from the Al neutral species and the Al2+ ion species is observed to coincide with current peaks through the plasma. Spectroscopic measurements indicate an Al2+ electronic temperature of 3 eV (and an Al+ electronic temperature of 1 eV) which, since local thermodynamic equilibrium (LTE) is applicable for the observed emission, provide a free electron temperature of 1 to 3 eV. A simple LTE model suggests an electron temperature of 1.2 eV for equal Al+ and Al2+ ion fractions. A floating double Langmuir probe measurement 1 mm in front of the laser ablation spot indicates an electron temperature of roughly 1 eV and an ion density of approximately 5*1014 cm-3 during the second current lobe.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/49189/2/ps950401.pd

Eigenvector localization as a tool to study small communities in online social networks

We present and discuss a mathematical procedure for identification of small "communities" or segments within large bipartite networks. The procedure is based on spectral analysis of the matrix encoding network structure. The principal tool here is localization of eigenvectors of the matrix, by means of which the relevant network segments become visible. We exemplified our approach by analyzing the data related to product reviewing on Amazon.com. We found several segments, a kind of hybrid communities of densely interlinked reviewers and products, which we were able to meaningfully interpret in terms of the type and thematic categorization of reviewed items. The method provides a complementary approach to other ways of community detection, typically aiming at identification of large network modules