The Mothers and Children’s Environmental Health (MOCEH) study

The MOCEH study is a prospective hospital- and community-based cohort study designed to collect information related to environmental exposures (chemical, biological, nutritional, physical, and psychosocial) during pregnancy and childhood and to examine how exposure to environmental pollutants affects growth, development, and disease. The MOCEH network includes one coordinating center, four local centers responsible for recruiting pregnant women, and four evaluation centers (a nutrition center, bio-repository center, neurocognitive development center, and environment assessment center). At the local centers, trained nurses interview the participants to gather information regarding their demographic and socioeconomic characteristics, complications related to the current gestation period, health behaviors and environmental factors. These centers also collect samples of blood, placenta, urine, and breast milk. Environmental hygienists measure each participant’s level of exposure to indoor and outdoor pollutants during the pre- and postnatal periods. The participants are followed up through delivery and until the child is 5 years of age. The MOCEH study plans to recruit 1,500 pregnant women between 2006 and 2010 and to perform follow-up studies on their children. We expect this study to provide evidence to support the hypothesis that the gestational environment has an effect on the development of diseases during adulthood. We also expect the study results to enable evaluation of latency and age-specific susceptibility to exposure to hazardous environmental pollutants, evaluation of growth retardation focused on environmental and genetic risk factors, selection of target environmental diseases in children, development of an environmental health index, and establishment of a national policy for improving the health of pregnant women and their children

Enhancing Railway Maintenance Safety Using Open-Source Computer Vision

As high-speed railways continue to be constructed, more maintenance work is needed to ensure smooth operation. However, this leads to frequent accidents involving maintenance workers at the tracks. Although the number of such accidents is decreasing, there is an increase in the number of casualties. When a maintenance worker is hit by a train, it invariably results in a fatality; this is a serious social issue. To address this problem, this study utilized the tunnel monitoring system installed on trains to prevent railway accidents. This was achieved by using a system that uses image data from the tunnel monitoring system to recognize railway signs and railway tracks and detect maintenance workers on the tracks. Images of railway signs, tracks, and maintenance workers on the tracks were recorded through image data. The Computer Vision OpenCV library was utilized to extract the image data. A recognition and detection algorithm for railway signs, tracks, and maintenance workers was constructed to improve the accuracy of the developed prevention system

GIS-based landslide susceptibility assessment in Seoul, South Korea, applying the radius of influence to frequency ratio analysis

The objective of this paper is to map landslide susceptibility using a statistical analysis model and the radius of influence within a geographic information systems environment. The statistical analysis included triggering factors (e.g., topography, land cover, forest, and soil properties) of adjacent areas, in addition to the landslide sites themselves. To estimate the probability of landslide occurrence using the radius of influence, and to produce a landslide susceptibility index (LSI), we performed frequency radio (FR) analysis by applying the radius of influence to the domain of specific training sites. Landslide susceptibility maps were generated for each radius of influence, ranging from 0 to 300 m in 30 m increments. We observed enhanced FR index values corresponding to reduced exaggeration of statistical anomalies within the proper radius of influence. It is referred that by adopting the radius of influence the classes that not only affect the landslide occurrence from the adjacent areas but also make anomaly errors can be taken into account in FR analysis. Moreover, comparing the FR values between adopting the optimum radius of influence or not, we inferred that the greater the gap, the bigger influence of adjacent areas the classes have. In the validation stage, we identified the optimum radius of influence by measuring the area beneath the relative operating characteristics curve. We found that the optimum radius of influence in the study area is 240 m, for which the LSI map is 5.95 % points more accurate than when not considering the radius of influence.N

Named Entity Correction in Neural Machine Translation Using the Attention Alignment Map

Neural machine translation (NMT) methods based on various artificial neural network models have shown remarkable performance in diverse tasks and have become mainstream for machine translation currently. Despite the recent successes of NMT applications, a predefined vocabulary is still required, meaning that it cannot cope with out-of-vocabulary (OOV) or rarely occurring words. In this paper, we propose a postprocessing method for correcting machine translation outputs using a named entity recognition (NER) model to overcome the problem of OOV words in NMT tasks. We use attention alignment mapping (AAM) between the named entities of input and output sentences, and mistranslated named entities are corrected using word look-up tables. The proposed method corrects named entities only, so it does not require retraining of existing NMT models. We carried out translation experiments on a Chinese-to-Korean translation task for Korean historical documents, and the evaluation results demonstrated that the proposed method improved the bilingual evaluation understudy (BLEU) score by 3.70 from the baseline

Functionalized semiconductor nanocrystal quantum dots for patterned, multilayered photovoltaic devices

We report an approach for nanostructured photovoltaic devices using functionalized semiconductor nanocrystal quantum dots (NQDs) by incorporation of the functional ligand t-butoxycarbonyl (t-BOC) which has an acid-labile moiety. This change in the surface chemistry results in the ability to photo-pattern the NQDs, where desired, for a number of optoelectronic device geometries with sub-micron patterning capability. This also enables the fabrication of multi-layered nanostructure photovoltaic devices. We demonstrate an improved photoconducting device, using the patterning and ligand modification process, as well as a bi-layered solar cell using CdTe and CdSe NQDs. The photoconductor has the metal semiconductor metal structure and it shows at least 3 times higher conductivity and photo-response at an electric field of 300kV/cm when using the t-BOC modified QDs. Moreover, the functionalized NQDs enable all solution processed multilayered and patterned structures without high temperature sintering or additional chemical treatment. By using this method, a bi-layered solar cell was fabricated. The preliminary result shows 0.05% solar conversion efficiency and an open circuit voltage of 0.72V under AM1.5G 1 sun illumination

Enhancement of the photovoltaic performance in PbS nanocrystal:P3HT hybrid composite devices by post-treatment-driven ligand exchange

A methodology for achieving versatile and facile ligand exchange by post-fabrication chemical treatment in PbS nanocrystal:poly(3-hexylthiophene) (P3HT) hybrid composite photovoltaic devices is demonstrated. We report a considerable improvement of the photovoltaic performance after post-fabrication chemical treatment using acetic acid to produce PbS nanocrystals surrounded by short-length ligands. Annealing induced morphological and photovoltaic performance changes in the resulting composite devices were investigated as a function of the annealing time

Binding Characteristics of Surface Ligands on PbSe QDs and Impact on Electrical Conductivity

ABSTRACTWe report the binding and conductivity characteristics of PbSe nanocrystal quantum dots which have different ligands on the surface. The PbSe nanocrystal quantum dots were surface functionalized using chemical treatment. The results of post-treatment analysis show that the PbSe surface can be successfully functionalized with various ligands based on thiol- and amine-molecules (e.g., oleic acid, dodecanethiol and butylamine). Conductivity measurements performed using a metal-semiconductor-metal structure indicate that there is an increase of conductivity as the length of the ligand connecting the quantum dots is reduced

Assessing and prioritizing environmental hazards associated with abandoned mines in Gangwon-do, South Korea: The Total Mine Hazards Index

This paper presents a new index, the Total Mine Hazards Index (TMHI), which has been developed to support reclamation planning in abandoned mining areas in Korea. The TMHI quantifies the extent of the hazards caused by mining in terms of five problem areas: (a) mine subsidence, (b) deforestation, (c) mine tailings, (d) waste rock dumps, and (e) mine water. These five mining hazards are statistically analyzed and the results are combined with Geographic Information Systems (GIS) modeling to prioritize the abandoned mines that pose the greatest hazard risk. A GIS database of mine-related information, including topographic data, land cover data, and road maps, is analyzed and used to evaluate the likely extent of mine-related pollution. As a case study, the TMHI is applied to Gangwon-do province in Korea, and the results show that the TMHI can be used to identify those mines most in need of attention and support mine reclamation planning by comprehensively quantifying the nature and extent of any hazards associated with abandoned mines.N

Enhanced electrochemical performance and interdiffusion behavior of sodium ions in onion-derived freeze-dried and KOH-activated carbon for sodium-ion battery anodes

Biomass-derived carbon materials are widely regarded as promising anode materials for sodium-ion batteries (SIBs) owing to their environmental friendliness, high electronic conductivity, stability, and low cost. However, their commercial application is restricted because of their low capacities and poor cycling stabilities. Heteroatom doping and increasing the active specific surface area of carbon materials have proven to be key to solving these problems. In this study, a facile activation and annealing process combined with freeze drying and KOH treatment was used to successfully prepare nitrogen-doped onion-derived carbon materials (dried onion (DO) and freeze-dried onion (FDO)) with high specific surface areas. The obtained carbon materials exhibited excellent electrochemical performances as anodes for SIBs, delivering high discharge reversible capacities of 140.5 (DO) and 151.4 (FDO) mAh/g at a current density of 0.05 A/g after 30 cycles. The capacities reached 45 (DO) and 66 (FDO) mAh/g at 30 A/g. Specifically, FDO//Na3V2(PO4)3@C full cells achieved a reversible capacity of 43.9 mAh/g with a specific energy of 91.5 Wh kg−1 at 5 C after 1,000 cycles, indicating that it provides broad prospects for the energy storage system of SIBs. © 2023 Elsevier B.V.FALS

sUA/sCr AUC, cut-off value, sensitivity, specificity.

sUA/sCr AUC, cut-off value, sensitivity, specificity.</p