Youngshin Han

Development of a novel peptide microarray for large-scale epitope mapping of food allergens

BACKGROUND The peptide microarray is a novel assay that facilitates high-throughput screening of peptides with a small quantity of sample. OBJECTIVE We sought to use overlapping peptides of milk allergenic proteins as a model system to establish a reliable and sensitive peptide microarray-based immunoassay for large-scale epitope mapping of food allergens. METHODS A milk peptide microarray was developed by using commercially synthesized peptides (20-mers, 3 offset) covering the primary sequences of alpha(s1)-casein, alpha(s2)-casein, beta-casein, kappa-casein, and beta-lactoglobulin. Conditions for printing and immunolabeling were optimized using a serum pool of 5 patients with milk allergy. Reproducibility of the milk peptide microarray was evaluated using replicate arrays immunolabeled with the serum pool, whereas specificity and sensitivity were assessed by using serial dilution of the serum pool and a peptide inhibition assay. RESULTS Our results show that epitopes identified by the peptide microarray were mostly consistent with those identified previously by SPOT membrane technology, but with specific binding to a few newly identified epitopes of milk allergens. Data from replicate arrays were reproducible (r > or = 0.92) regardless of printing lots, immunolabeling, and serum pool batches. Using the serially diluted serum pool, we confirmed that IgE antibody binding detected in the array was specific. Peptide inhibition of IgE binding to the same peptide and overlapping peptides further confirmed the specificity of the array. CONCLUSION A reliable peptide microarray was established for large-scale IgE epitope mapping of milk allergens, and this robust technology could be applied for epitope mapping of other food allergens.

On the repair of memory cells with spare rows and columns for yield improvement

As the density of memory chips increases, the probability of having defective components is also increased. It would be impossible for us to repair a memory device if it has numerous defects that cannot be dealt with properly. However, in case of a small number of defects, it is desirable to reuse a defective die (standard unit measuring a device on a wafer) after repair rather than to discard it, because reuse is an essential element for memory device manufactures to cut costs effectively. To perform the reuse, laser-repair process and redundancy analysis for setting an accurate target in the laser-repair process is needed. In this paper new approach for the repair of large random access memory (RAM) devices in which redundant rows and columns are added as spares. So, cost reduction was attempted by reducing time in carrying out a new type of redundancy analysis after simulating each defect.

Current status of managing food allergies in schools in Seoul, Korea

Recently the need to manage food allergies in schools has been growing. This study aimed to examine the current status of managing food allergies in schools in Seoul, Korea. A questionnaire survey was conducted in cooperation with the School Dietician Association during April 2009. Among the participating 154 schools, a total of 109 (71%) were determining students’ food allergy status through parental surveys based on self-reported food allergies. A total of 72 (47%) had experienced student visits to a school health room due to food allergies within one year before the survey. Over 80 percent of the schools relied on self-care only without any school-wide measures for food allergies in place. Among the 890 menu items most frequently served in school lunch programs, a total of 664 (75%) were found to contain more than one food allergen. It is highly suggested that preventive plans and treatment measures should be established to manage food allergies in schools.

Association of carbon monoxide levels with allergic diseases in children.

BACKGROUND Air pollution is regarded as a potential reason for the development or aggravation of allergic diseases. OBJECTIVE To investigate the relationship between exposure to outdoor air pollution during the first year of life and the development of allergic diseases, and to determine the association between outdoor air pollution near the residence and recent symptoms of allergic diseases in children. METHODS A nationwide cross-sectional survey was conducted in 6- to 7-year-old children. Among them, subjects who had been born (n = 1828) or lived (n = 1894) within 2 km of the nearest air quality monitoring sites were selected. The prevalence of allergic diseases was assessed by using questionnaires. Each subject was examined by pediatricians to determine the presence of eczema. Publicly available data were used regarding the daily ambient concentrations of sulfur dioxide, nitrogen dioxide, ozone, carbon monoxide (CO), and particulate matter. RESULTS For a 100 ppb increase in the mean daily CO level during the first year of life, the adjusted odds ratio for lifetime allergic rhinitis was 1.10 (95% confidence interval, 1.03-1.19). For a 1 ppm increase in the annual average CO level during the past 12 months, the adjusted odds ratio for the presence of atopic dermatitis on the day of the survey was 8.11 (95% confidence interval, 1.06-62.12). However, the other air pollutants showed no statistical significance. CONCLUSIONS Higher exposure to CO during infancy increased the risk of development of allergic rhinitis. The risk of current atopic dermatitis symptoms increased in children who were exposed to higher CO levels during the past 12 months.

Implementation of Cloud Computing Environment for Discrete Event System Simulation using Service Oriented Architecture

This paper presents a cloud computing architecture for discrete event system modeling and simulation. Simulators with models used in the cloud computing are considered as web services which are accessed via web browser. This environment supports the simulation of homogeneous or heterogeneous models without much knowledge of discrete event modeling and simulation.

Full fabrication simulation of 300mm wafer focused on AMHS (automated material handling systems)

Semiconductor fabrication lines are organized using bays, equipment, and stockers. Most 300mm wafer lines use AMHS (Automated Material Handling System) for inter-bay and intra-bay lot transportation. In particular, the inter-bay AMHS moves lots between stockers, whereas intra-bay AMHS moves lots between stockers and tools, or between tools within the same bay. The key concern for manufacturer is how to raise productivity and to reduce turn-around time. This paper presents a simulation to reduce turn around time and raise productivity by reducing the delivery time (which affects AMHS).

Automatic classification using decision tree and support vector machine

The EDS wafer test yield is the most important criteria to evaluate FABs productivity, so the manufacturing operations main purpose is to secure new product yield early and maintaining the yield of mass-produced products high. Defining a failed characteristic thats compatible to the device and classifying wafers depending on failure type helps tasks searching for error from FAB become automated. This would be more efficient then existing failed analysis operations and strive to become the basis for improvement in yield and quality. For this method, this research is trying to use a high speed recognition algorithm called SVM (support vector machine) that will define wafers failed type and automatically classify each one.

Automatic detection of failure patterns using data mining

In the semiconductor manufacturing, yield enhancement is an important issue. It is ideal to prevent all failures. However, when a failure occurs, it is important to quickly specify the cause stage and take countermeasures. Reviewing wafer level and composite lot level yield patterns has always been an effective way of identifying yield inhibitors and driving process improvement. This process is very time consuming and as such generally occurs only when the overall yield of a device has dropped significantly enough to warrant investigation. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. The automatic method of failure pattern extraction from fail bit map provides reduced time to analysis and facilitates yield enhancement. This paper describes the techniques to automatically recognize and classifies a failure pattern using a fail bit map, a new simple schema which facilitates the failure analysis.

Flight Simulation on Tiled Displays with Distributed Computing Scheme

Flight simulator is based on real aircrafts. The main purpose of flight simulator is to prevent accidents when people control real flight through the training with various unexpected scenarios during flight. It is difficult to handle large scale geographical data on ordinary personal computer. Therefore, we propose distributed flight simulation which provides wider screen view on tiled displays and high system performance with distributed computing environment.

A production planning methodology for semiconductor manufacturing based on simulation and marketing pattern

To make production and equipment investments plans in semiconductor lines, the implementation of many variables is needed. These factors bring many changes and the result is hard to predict. It is difficult to define a standard because there are many influencing factors to make a prediction. This project established semiconductor production plans using the marketing pattern references on the past to satisfy all conditions from the factors. We come up with thesis on reasonable and standardized processes.