INVESTIGATION ON THE SPATIAL AND TEMPORAL VARIATIONS OF VOLATILE ORGANIC COMPOUNDS (VOCs) IN ULSAN

Department of Urban and Environmental Engineering(Environmental Science and Engineering)Large amounts of Volatile Organic Compounds (VOCs) are emitted from industrial facilities, and they can cause harmful effects to human health. Once emitted to the atmosphere, VOCs are dispersed into surrounding areas and directly inhaled by residents. Ulsan, known as the largest industrial city of South Korea, has many kinds of factories related to petrochemical, automobile, non-ferrous, and shipbuilding industries. Large VOC emissions are expected in Ulsan, thus continuous and intensive monitoring is required. The aim of this study is to investigate the levels, pattern, spatial distribution, main sources, and risk levels of VOCs in Ulsan, South Korea. In this study, VOC monitoring in Ulsan was conducted using passive air sampler (Radiello 130 packed with 530 mg of active charcoal with particle size of 35-50 mesh). The samplers were deployed at 14 sites in Ulsan during summer (02-31 July (30 days) and 31 July-29 August, 2014 (30 days)), fall (08 October-07 November (30 days) and 07 November-05 December, 2014 (30 days)), winter (08 January-03 February (26 days) and 03 February-03 March, 2015 (30 days)), and spring (10 April-08 May (28 days) and 08 May-07 June, 2015 (30 days)). Sampling sites were divided into urban (U1-U8) and industrial (I1-I6) areas. The target compounds were 28 VOCs which were classified into three groups, including aromatic, halogenated, and others (alkene and oxygenated). Radiello cartridges were extracted, and the extracts were analyzed using a gas chromatograph/mass spectrometer (Agilent 7890A/5975C). The target VOCs were generally detected at all sampling sites, indicating that VOCs are ubiquitous in Ulsan and not good for human health. Particularly, there were no significant differences in seasonal concentration of VOCs, because many industrial facilities, located in Ulsan, emit VOCs continuously regardless of weather. Among target groups, aromatic groups accounted for most of VOCs (66-86%), in detail, concentration of toluene was highest at all the sampling sites over the sampling periods. Also, most of total VOC concentrations were relatively high at industrial sites and low at urban sites. According to the spatial distributions of VOCs, all major industries of Ulsan seem to be the important VOC sources, especially automobile industrial complexes. To identify main sources of VOCs, a variety of statistical tools were used. As a result, non-traffic sources were dominant in Ulsan, and several compounds had a good correlation, indicating similar emission sources. Although there are many kinds of industrial facilities in Ulsan, risk was not serious according to risk assessment of benzene, toluene, ethylbenzene, and xylenes (BTEX). Through this preliminary study, we could identify seasonal major sources and risk levels of VOCs in Ulsan. This study is the first comprehensive study for VOCs including high resolution monitoring in Ulsan, therefore, it can be applied to other national industrial complexes in South Korea.ope

Statistical Models for Hot Electron Degradation in Nano-Scaled MOSFET Devices

In a MOS structure, the generation of hot carrier interface states is a critical feature of the item\u27s reliability. On the nano-scale, there are problems with degradation in transconductance, shift in threshold voltage, and decrease in drain current capability. Quantum mechanics has been used to relate this decrease to degradation, and device failure. Although the lifetime, and degradation of a device are typically used to characterize its reliability, in this paper we model the distribution of hot-electron activation energies, which has appeal because it exhibits a two-point discrete mixture of logistic distributions. The logistic mixture presents computational problems that are addressed in simulation

Clinical Significance of p16 Protein Expression Loss and Aberrant p53 Protein Expression in Pancreatic Cancer

Pancreatic cancer is a disease with poor prognosis mainly due to low resection rates and late diagnosis. To increase resectability and improve survival rates, a better understanding of pancreatic cancer pathogenesis and more effective screening techniques are required. New methods, such as genetic and molecular alterations, may suggest novel approaches for pancreatic cancer diagnosis and treatment. We immunohistochemically investigated 44 formalin-fixed, paraffin-embedded specimens of pancreatic ductal adenocarcinoma using monoclonal anti-p16 antibodies and monoclonal anti-p53 antibodies. The expressions of p16 and p53 proteins were compared using the Chi-square test with SPSS. Disease-free survival was analyzed using the Kaplan-Meier method, verified by the Log-Rank test. Loss of p16 expression was noted in 20 (45.5%) cases and aberrant p53 protein expression was detected in 14 (31.8%) cases. Loss of p16 expression was associated with a higher incidence of lymph node metastasis (p=0.040) and a more advanced stage (p=0.015), although there was no significant correlation between p16 expression and survival. Aberrant p53 protein expression correlated with histologic grade (p=0.038). Disease-free survival rate was significantly lower in the aberrant p53 protein positive group compared to the negative group (p=0.029). From our results, we suggest that p53 is not a prognostic factor; however, p16 and p53 genes do play important roles in the progression of pancreatic ductal adenocarcinoma

How to Mask in Error Correction Code Transformer: Systematic and Double Masking

In communication and storage systems, error correction codes (ECCs) are pivotal in ensuring data reliability. As deep learning's applicability has broadened across diverse domains, there is a growing research focus on neural network-based decoders that outperform traditional decoding algorithms. Among these neural decoders, Error Correction Code Transformer (ECCT) has achieved the state-of-the-art performance, outperforming other methods by large margins. To further enhance the performance of ECCT, we propose two novel methods. First, leveraging the systematic encoding technique of ECCs, we introduce a new masking matrix for ECCT, aiming to improve the performance and reduce the computational complexity. Second, we propose a novel transformer architecture of ECCT called a double-masked ECCT. This architecture employs two different mask matrices in a parallel manner to learn more diverse features of the relationship between codeword bits in the masked self-attention blocks. Extensive simulation results show that the proposed double-masked ECCT outperforms the conventional ECCT, achieving the state-of-the-art decoding performance with significant margins.Comment: 8 pages, 5 figure

Transcriptional regulatory networks underlying the reprogramming of spermatogonial stem cells to multipotent stem cells

Spermatogonial stem cells (SSCs) are germline stem cells located along the basement membrane of seminiferous tubules in testes. Recently, SSCs were shown to be reprogrammed into multipotent SSCs (mSSCs). However, both the key factors and biological networks underlying this reprogramming remain elusive. Here, we present transcriptional regulatory networks (TRNs) that control cellular processes related to the SSC-to-mSSC reprogramming. Previously, we established intermediate SSCs (iSSCs) undergoing the transition to mSSCs and generated gene expression profiles of SSCs, iSSCs and mSSCs. By comparing these profiles, we identified 2643 genes that were up-regulated during the reprogramming process and 15 key transcription factors (TFs) that regulate these genes. Using the TF-target relationships, we developed TRNs describing how these TFs regulate three pluripotency-related processes (cell proliferation, stem cell maintenance and epigenetic regulation) during the reprogramming. The TRNs showed that 4 of the 15 TFs (Oct4/Pou5f1, Cux1, Zfp143 and E2f4) regulated cell proliferation during the early stages of reprogramming, whereas 11 TFs (Oct4/Pou5f1, Foxm1, Cux1, Zfp143, Trp53, E2f4, Esrrb, Nfyb, Nanog, Sox2 and Klf4) regulated the three pluripotency-related processes during the late stages of reprogramming. Our TRNs provide a model for the temporally coordinated transcriptional regulation of pluripotency-related processes during the SSC-to-mSSC reprogramming, which can be further tested in detailed functional studies.111Ysciescopuskc