Utilizing Artificial Neural Networks for Establishing Hearing-Loss Predicting Models Based on a Longitudinal Dataset and Their Implications for Managing the Hearing Conservation Program

Background@#Though the artificial neural network (ANN) technique has been used to predict noise-induced hearing loss (NIHL), the established prediction models have primarily relied on cross-sectional datasets, and hence, they may not comprehensively capture the chronic nature of NIHL as a disease linked to long-term noise exposure among workers. @*Methods@#A comprehensive dataset was utilized, encompassing eight-year longitudinal personal hearing threshold levels (HTLs) as well as information on seven personal variables and two environmental variables to establish NIHL predicting models through the ANN technique. Three subdatasets were extracted from the afirementioned comprehensive dataset to assess the advantages of the present study in NIHL predictions. @*Results@#The dataset was gathered from 170 workers employed in a steel-making industry, with a median cumulative noise exposure and HTL of 88.40 dBA-year and 19.58 dB, respectively. Utilizing the longitudinal dataset demonstrated superior prediction capabilities compared to cross-sectional datasets. Incorporating the more comprehensive dataset led to improved NIHL predictions, particularly when considering variables such as noise pattern and use of personal protective equipment. Despite fluctuations observed in the measured HTLs, the ANN predicting models consistently revealed a discernible trend. @*Conclusions@#A consistent correlation was observed between the measured HTLs and the results obtained from the predicting models. However, it is essential to exercise caution when utilizing the model-predicted NIHLs for individual workers due to inherent personal fluctuations in HTLs. Nonetheless, these ANN models can serve as a valuable reference for the industry in effectively managing its hearing conservation program.

Analysis of Variation in Total Airborne Bacteria Concentration to Assess the Performance of Biological Safety Cabinets in Microbial Laboratories

BACKGROUND: The purpose of this study was to compare the concentration of total airborne bacteria (TAB) in biosafety cabinets (BSCs) at universities and hospital microbial laboratories to assess the performance of BSCs. METHODS: TAB was determined by using the single-stage Anderson sampler (BioStage Viable Cascade Impactor). The samples were obtained three times (with the BSC turned off and the shield open; with the BSC turned off and the shield closed; and with the BSC tuned on and operating) from the areas in front of 11 BSCs. RESULTS: TAB concentrations of accredited and nonaccredited BSCs were determined. No significant differences were observed in the TAB concentrations of the accredited BSCs and the nonaccredited BSCs for the areas outside the BSCs in the laboratories (p > 0.05). TAB concentrations for the BSCs sampled with the shield open and the instrument turned off showed differences based on the sampling site outside the BSC in each laboratory. CONCLUSION: These results imply that TAB concentration is not altered by the performance of the BSCs or TAB itself and/or concentration of TAB outside the BSC is not a good index of BSC performance.

Outdoor (1-->3)-beta-D-glucan Levels and Related Climatic Factors / 예방의학회지

OBJECTIVES: To evaluate the monthly variation in the airborne (1-->3)-beta-D-glucan level throughout one year and its relationship with climatic factors (temperature, relative humidity, wind speed, hours of daylight, cloud cover, and pollen counts). METHODS: A total of 106 samples were collected using a two-stage cyclone sampler at five outdoor sampling locations (on top of 5 university buildings). The kinetic limulus amebocyte lysate assay was used to obtain (1-->3)-beta-D-glucan levels. RESULTS: Airborne (1-->3)-beta-D-glucan levels were significantly higher in the spring, particularly in April, and temperature was significantly related to (1-->3)-beta-D-glucan levels (r =0.339, p3)-beta-D-glucan levels may be highest in the spring, and outdoor temperature may influence (1-->3)-beta-D-glucan levels.

Review on Potential Risk Factors in Wafer Fabrication Process of Semiconductor Industry / 대한산업의학회지

OBJECTIVES: To associate work in the semiconductor industry, including silicon wafer fabrication, with cancer risks or mortality and other adverse health effects, the operation of wafer fabrication should initially be understood. A detailed study on the fabrication operation allows retrospective exposure to be assessed and wafer fabrication workers to be classified into similar exposure groups. Therefore, the objective of this study was to comprehensively review silicon wafer fabrication operations and related hazardous materials and agents. METHODS: The literatures related to semiconductor industry processes were reviewed from an occupational health viewpoint based on wafer manufacturing, wafer fabrication and packaging. The focus was especially related to the hazardous materials used in wafer fabrication industries. RESULTS: During the fabrication of silicon wafers, many toxic chemicals, a strong electric field and hazardous equipment are used. The process allows the integration of a three-dimensional array of electric circuits onto a silicon wafer substrate. Wafers are sliced from single crystal silicon and subject to a series of steps during the fabrication process, which alternatively adds and then selectively removes materials in layers from the surface of the wafer to create different parts of the completed integrated circuit. There are four major steps in this process; patterning, junction formation, thin film and metallization. CONCLUSIONS: In order to associate exposure to the hazard agents generated during wafer fabrication operations with adverse health effects the details of the operation should be completely studied, which will be helpful in both exposure assessments and epidemiological studies.

Vaporization and Conversion of Ethanolamines used in Metalworking Operations

OBJECTIVES: This study examined how ethanolamines (EAs) with the same functional alcohol group (HOCH2CH2), such as mono-EA (MEA), di-EA (DEA), and tri-EA (TEA), in water-based metalworking fluids (wbMWFs) are vaporized, condensed, and transformed by heat generated during metalworking. METHODS: Two types of experimental apparatus were manufactured to achieve these objectives. RESULTS: Vaporization tests using a water bath showed that the vaporization rate increased markedly from 0.19 mg/m2.min at 23.5degrees C to 8.04 mg/m2.min at 60degrees C. Chamber tests with a heat bulb revealed that "spiked" MEA was fully recovered, while only 13.32% of DEA and no TEA were recovered. Interestingly, non-spiked types of EAs were detected, indicating that heat could convert EAs with more alcohol groups (TEA or DEA) into other EAs with fewer group(s) (DEA or MEA). The EA composition in fresh fluid was 4% DEA, 66% TEA, and 30% MEA, and in used fluids (n = 5) was 12.4% DEA, 68% TEA, and 23% MEA. Conversion from TEA into DEA may therefore contribute to the DEA increment. Airborne TEA was not detected in 13 samples taken from the central coolant system and near a conveyor belt where no machining work was performed. The DEA concentration was 0.45 mg/m3 in the only two samples from those locations. In contrast, airborne MEA was found in all samples (n = 53) regardless of the operation type. CONCLUSION: MEAs easily evaporated even when MWFs were applied, cleaned, refilled, and when they were in fluid storage tanks without any metalworking being performed. The conversion of TEA to DEA and MEA was found in the machining operations.