Analysis of a successful inspection program

Litton Data Systems has institutionalized the inspection process, and achieved dramatic results in terms of defect prevention and cost savings thus far. Additionally, several findings have been gleaned from an analysis to optimize the process. Over 300 inspections have been performed over the last two years on many types of documents, and this paper describes some quantitative results to-date from the initial 'champion' project

Reviews

Judith Jeffcoate, Multimedia in Practice ‐Technology and Applications, BCS Practitioner Series, Prentice‐Hall International, 1995. ISBN: 0–13–123324–6. £24.95

Ariel - Volume 9 Number 1

Executive Editor Emily Wofford Business Manager Fredric Jay Matlin University News John Patrick Welch World News George Robert Coar Editorial Editor Steve Levine Feature Brad Feldstein Mark Rubin Graphics Steve Hulkower Photo Rick Spaide Circulation Lee Wugofsk

The anatomy of tubercles: A corrosion study in a fresh water estuary

The structure and mineralogy of corrosion products formed on carbon steel coupons exposed in Duluth Superior Harbor (DSH, USA), were investigated and compared with corrosion products on similar substrata from other locations. Corrosion products in DSH form within a few months each year and are removed by ice scour and reform. The corrosion products formed in DSH are tubercles with an outer surface, an inner shell of magnetite, and a core of iron(III) oxyhydroxides, goethite, and lepidocrocite, in association with stalks produced by bacteria. In general, the tubercles formed in DSH are similar in morphology and mineralogy to corrosion products described for carbon steel and cast iron exposed to treated waters in decades-old drinking water and cooling water systems. DSH tubercles are unique in several structural details. DSH tubercles increase areal coverage of the substratum by consolidation of tubercles. Furthermore, the core material extends into the pit and is an exact replica of the pit profile

High Power Density from a Miniature Microbial Fuel Cell Using \u3ci\u3eShewanella oneidensis\u3c/i\u3e DSP10

A miniature microbial fuel cell (mini-MFC) is described that demonstrates high output power per device crosssection (2.0 cm2) and volume (1.2 cm3). Shewanella oneidensis DSP10 in growth medium with lactate and buffered ferricyanide solutions were used as the anolyte and catholyte, respectively. Maximum power densities of 24 and 10 mW/m2 were measured using the true surface areas of reticulated vitreous carbon (RVC) and graphite felt (GF) electrodes without the addition of exogenous mediators in the anolyte. Current densities at maximum power were measured as 44 and 20 mA/m2 for RVC and GF, while short circuit current densities reached 32 mA/m2 for GF anodes and 100 mA/m2 for RVC. When the power density for GF was calculated using the cross sectional area of the device or the volume of the anode chamber, we found values (3 W/m2, 500 W/m3) similar to the maxima reported in the literature. The addition of electron mediators resulted in current and power increases of 30-100%. These power densities were surprisingly high considering a pure S. oneidensis culture was used. We found that the short diffusion lengths and high surface-area-to-chamber volume ratio utilized in the mini-MFC enhanced power density when compared to output from similar macroscopic MFCs

High Power Density from a Miniature Microbial Fuel Cell Using \u3ci\u3eShewanella oneidensis\u3c/i\u3e DSP10

A miniature microbial fuel cell (mini-MFC) is described that demonstrates high output power per device crosssection (2.0 cm2) and volume (1.2 cm3). Shewanella oneidensis DSP10 in growth medium with lactate and buffered ferricyanide solutions were used as the anolyte and catholyte, respectively. Maximum power densities of 24 and 10 mW/m2 were measured using the true surface areas of reticulated vitreous carbon (RVC) and graphite felt (GF) electrodes without the addition of exogenous mediators in the anolyte. Current densities at maximum power were measured as 44 and 20 mA/m2 for RVC and GF, while short circuit current densities reached 32 mA/m2 for GF anodes and 100 mA/m2 for RVC. When the power density for GF was calculated using the cross sectional area of the device or the volume of the anode chamber, we found values (3 W/m2, 500 W/m3) similar to the maxima reported in the literature. The addition of electron mediators resulted in current and power increases of 30-100%. These power densities were surprisingly high considering a pure S. oneidensis culture was used. We found that the short diffusion lengths and high surface-area-to-chamber volume ratio utilized in the mini-MFC enhanced power density when compared to output from similar macroscopic MFCs

Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity:The Mobile Parkinson Disease Score

IMPORTANCE: Current Parkinson disease (PD) measures are subjective, rater-dependent, and assessed in clinic. Smartphones can measure PD features, yet no smartphone-derived rating score exists to assess motor symptom severity in real-world settings. OBJECTIVES: To develop an objective measure of PD severity and test construct validity by evaluating the ability of the measure to capture intraday symptom fluctuations, correlate with current standard PD outcome measures, and respond to dopaminergic therapy. DESIGN, SETTING, AND PARTICIPANTS: This observational study assessed individuals with PD who remotely completed 5 tasks (voice, finger tapping, gait, balance, and reaction time) on the smartphone application. We used a novel machine-learning-based approach to generate a mobile Parkinson disease score (mPDS) that objectively weighs features derived from each smartphone activity (eg, stride length from the gait activity) and is scaled from 0 to 100 (where higher scores indicate greater severity). Individuals with and without PD additionally completed standard in-person assessments of PD with smartphone assessments during a period of 6 months. MAIN OUTCOMES AND MEASURES: Ability of the mPDS to detect intraday symptom fluctuations, the correlation between the mPDS and standard measures, and the ability of the mPDS to respond to dopaminergic medication. RESULTS: The mPDS was derived from 6148 smartphone activity assessments from 129 individuals (mean [SD] age, 58.7 [8.6] years; 56 [43.4%] women). Gait features contributed most to the total mPDS (33.4%). In addition, 23 individuals with PD (mean [SD] age, 64.6 [11.5] years; 11 [48%] women) and 17 without PD (mean [SD] age 54.2 [16.5] years; 12 [71%] women) completed in-clinic assessments. The mPDS detected symptom fluctuations with a mean (SD) intraday change of 13.9 (10.3) points on a scale of 0 to 100. The measure correlated well with the Movement Disorder Society Unified Parkinson Disease's Rating Scale total (r = 0.81; P < .001) and part III only (r = 0.88; P < .001), the Timed Up and Go assessment (r = 0.72; P = .002), and the Hoehn and Yahr stage (r = 0.91; P < .001). The mPDS improved by a mean (SD) of 16.3 (5.6) points in response to dopaminergic therapy. CONCLUSIONS AND RELEVANCE: Using a novel machine-learning approach, we created and demonstrated construct validity of an objective PD severity score derived from smartphone assessments. This score complements standard PD measures by providing frequent, objective, real-world assessments that could enhance clinical care and evaluation of novel therapeutics