Prevalence of early and late age-related macular degeneration in a rural population in Northern India: The INDEYE Feasibility Study

PURPOSE. To assess the prevalence of age-related macular degeneration (AMD) in a rural population in Northern India. METHODS. In a pilot feasibility study, 1443 people (median age, 60 years; 52% women), were identified from enumeration of the 50+ age group in 11 randomly sampled villages from a rural, periurban district of Haryana, Northern India. Of those identified, 87% attended an eye examination that included digital fundus photography. Fundus images were graded at a single reading center using definitions from the Wisconsin Age-Related Maculopathy Grading System. RESULTS. Fundus photographs were available for 1101 participants. Overall, 28.8% of participants had ungradable fundus images due to cataract. Including all with ungradable images in the denominator, the prevalence of soft drusen was 34.0% (95% confidence interval [CI] 26.1–42.9); of soft indistinct drusen, 2.2% (95% CI, 1.1–4.4); and of pigmentary irregularities, 10.8% (95% CI, 7.1–16.1). There were 15 (1.4%) cases of late-stage AMD (95% CI, 0.8–2.3) with the prevalence rising from 0.4% in the 50- to 59-year age range to 4.6% in those aged 70 years or older. CONCLUSIONS. Drusen and pigmentary irregularities are common among the rural northern Indian population. The prevalence of late AMD is similar to that encountered in Western settings and is likely to contribute significantly to the burden of vision loss in older people in the developing world.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.