Yeonju Go

The life cycle assessment (LCA) serves as a crucial tool for assessing the environmental impact of products, with recent emphasis on polyethylene terephthalate (PET) bottles. Our meta-analytical review of 14 LCA research papers (2010–2022) on PET bottles, aligned with PRISMA guidelines, spans six phases: raw material production (MP), bottle production (BP), distribution and transportation (DT), collection and transport (CT), waste management (WM), and environmental benefits (EB). Utilizing the global warming potential (GWP) as the indicator, our study harmonized data into a consistent functional unit, revealing an average emission of 5.1 kg CO2 equivalent per 1 kg of PET bottles. Major contributors to global warming were identified across the MP, BP, and DT phases. While the MP and BP phases exhibited low variability due to uniform processes, the CT, WM, and EB phases displayed higher variability due to scenario considerations. A comparison with Korean environmental product declaration data affirmed the methodology’s practical utility. Our approach offers potential applicability in diverse product category assessments, emphasizing its relevance for informed decision-making in sustainable product development.

Brain-computer interface (BCI) technology facilitates communication between the human brain and computers, primarily utilizing electroencephalography (EEG) signals to discern human intentions. Although EEG-based BCI systems have been developed for paralysis individuals, ongoing studies explore systems for speech imagery and motor imagery (MI). This study introduces FingerNet, a specialized network for fine MI classification, departing from conventional gross MI studies. The proposed FingerNet could extract spatial and temporal features from EEG signals, improving classification accuracy within the same hand. The experimental results demonstrated that performance showed significantly higher accuracy in classifying five finger-tapping tasks, encompassing thumb, index, middle, ring, and little finger movements. FingerNet demonstrated dominant performance compared to the conventional baseline models, EEGNet and DeepConvNet. The average accuracy for FingerNet was 0.3049, whereas EEGNet and DeepConvNet exhibited lower accuracies of 0.2196 and 0.2533, respectively. Statistical validation also demonstrates the predominance of FingerNet over baseline networks. For biased predictions, particularly for thumb and index classes, we led to the implementation of weighted cross-entropy and also adapted the weighted cross-entropy, a method conventionally employed to mitigate class imbalance. The proposed FingerNet involves optimizing network structure, improving performance, and exploring applications beyond fine MI. Moreover, the weighted Cross Entropy approach employed to address such biased predictions appears to have broader applicability and relevance across various domains involving multi-class classification tasks. We believe that effective execution of motor imagery can be achieved not only for fine MI, but also for local muscle MI

Preterm birth (PTB) refers to delivery before 37 weeks of gestation. Premature neonates exhibit higher neonatal morbidity and mortality rates than term neonates; therefore, predicting and preventing PTB are important. In this study, we investigated the potential of using short-chain fatty acid (SCFA) levels, specific vaginal microbiota-derived metabolites, as a biomarker in predicting PTB using gas chromatography/mass spectrometry. Cervicovaginal fluid (CVF) was collected from 89 pregnant women (29 cases of PTB vs. 60 controls) without evidence of other clinical infections, and SCFA levels were measured. Furthermore, the PTB group was divided into two subgroups based on birth timing after CVF sampling: delivery ≤ 2 days after sampling (n = 10) and ≥2 days after sampling (n = 19). The concentrations of propionic acid, isobutyric acid, butyric acid, valeric acid, hexanoic acid, and heptanoic acid were significantly higher in the PTB group than in the term birth (TB) group (p < 0.05). In particular, the concentrations of propionic acid, isobutyric acid, hexanoic acid, and heptanoic acid were continuously higher in the PTB group than in the TB group (p < 0.05). In the delivery ≤ 2 days after sampling group, the propionic acid, isobutyric acid, hexanoic acid, and heptanoic acid levels were significantly higher than those in the other groups (p < 0.05). This study demonstrated a significant association between specific SCFAs and PTB. We propose these SCFAs as potential biomarkers for the prediction of PTB.

Vulvovaginal candidiasis (VVC) is a genital infection caused by Candida albicans (C. albicans). Weissella confusa WIKIM51 (Wilac D001) is known to be detected in dandelion kimchi, produce lactic acid, and have an anti−inflammatory ability; however, its diverse antifungal effects have not been studied. Here, we investigated the antifungal effect of Wilac D001 in C. albicans compared to Lactobacillus species on vaginal epithelial cells (VECs). To test the antifungal ability of Wilac D001 against C. albicans on VECs, an adhesion test, pro-inflammatory cytokines (interleukin (IL)-6 and IL-8) analysis, and a disk diffusion test were performed. The acid tolerance test was conducted to investigate the viability of Wilac D001 in various acidic conditions. Lactobacillus reuteri (L. reuteri) and L. rhamnosus were used as positive controls. Wilac D001 showed the capacity to inhibit the colonization of C. albicans by adhering to VECs, with an inhibitory effect similar to that of positive controls. Both pro−inflammatory cytokines including IL−6 and IL−8 concentrations were significantly decreased when Wilac D001 was treated on C. albicans-infected VECs, respectively (p < 0.001). The result of the disk diffusion test indicates that the inhibitory ability of Wilac D001 is comparable to L. reuteri and L. rhamnosus on agar plates infected with C. albicans. Our results demonstrate that Weissella confusa WIKIM51 has antifungal effects against VECs infected by C. albicans.

This paper proposes a deep neural network (DNN)-based calibration factor estimation for an effective signal-to-interference-plus-noise ratio (SINR) mapping in a channel quality indicator (CQI) selection of fifth-generation new radio (5G NR). In 5G NR, a receiver can report CQI to a transmitter, and adaptive modulation and coding (AMC) is performed in the transmitter. The CQI can be selected using an effective SINR mapping (ESM) scheme in the receiver. The ESM scheme can compress the received SINRs into an effective SINR. Further, a calibration factor is required to improve the accuracy of ESM. The optimal value of the calibration factor may differ according to the channel environment between the transmitter and receiver. In this paper, the proposed scheme can estimate the optimal calibration factor using the DNN model. Simulation results show that the proposed DNN-based scheme outperforms the conventional scheme using the predefined calibration factor.

As more distributed deep learning (DDL) jobs run in public clouds, their effective scheduling becomes a major challenge. Current studies prioritize the execution of jobs with less remaining time, which is known to be the best in reducing average job completion time (JCT). However, we observe that this approach does not work when the preemption for pausing and loading jobs weighs in; sometimes, the preemption overheads of DDL jobs take up to hundreds of seconds. This results in very ineffective scheduling, so in some cases, the first-in-first-out policy performs much better. This paper proposes a new scheduling framework called Xion that takes into account the preemption overheads and only preempts DDL jobs when it is beneficial. Our evaluation results demonstrate that Xion effectively reduces the average JCT by 19% and improves the waiting time by 1.64×.

We report on a systematic study of double-gap and four-gap phenolic resistive plate chambers (RPCs) for the Phase-2 upgrade of the CMS muon system at high η. In the present study, we constructed real-sized double-gap and four-gap RPCs with gap thicknesses of 1.6 and 0.8 mm, respectively, with 2-mm-thick phenolic high-pressure-laminated (HPL) plates. We examined the prototype RPCs with cosmic rays and with 100-GeV muons provided by the SPS H4 beam line at CERN. To examine the rate capability of the prototype RPCs both at Korea University and at the CERN GIF++ facility, the chambers were irradiated with 137Cs sources providing maximum gamma rates of about 1.5 kHz cm−2. For the 1.6-mm-thick double-gap RPCs, we found the relatively high threshold on the produced detector charge was conducive to effectively suppressing the rapid increase of strip cluster sizes of muon hits with high voltage, especially when measuring the narrow-pitch strips. The gamma-induced currents drawn in the four-gap RPC were about one-fourth of those drawn in the double-gap RPC. The rate capabilities of both RPC types, proven through the present testing using gamma-ray sources, far exceeded the maximum rate expected in the new high-η endcap RPCs planned for future phase-II runs of the Large Hadron Collider (LHC).

애완동물 건강에 대한 세계적인 관심이 높아지면서 이 분야에서 AI의 중요성이 커졌다. 하지만 수의학 인공지능은 인간 의학 AI만큼 광범위하게 연구되지 않았다. 따라서, 우리는 AI를 애완동물 건강 관리에 적용했고, 특히 컴퓨터 비전을 이용한 진단 흐름을 제시하였다. 진단 흐름은 데이터 수집, 데이터 전처리, 객체 감지 및 분류, 영상 분할로 구성된다. 분류를 위해 X선 영상에서 심장을 감지하고 정상 또는 비정상으로 분류하기 위해 YOLOv5를 사용하였다. 이후 비정상으로 분류된 경우 영상 분할은 좌심방 확대 정도를 시각적으로 보여준다. 분류 정확도는 정상 클래스의 경우 0.8800, 비정상 클래스의 경우 0.8933을 달성하여 전체 분류 정확도는 0.8866이다. 추가 분류 메트릭에는 f1 점수 0.8864 및 AUC 점수 0.8866이 포함된다. 영상 분할 성능은 주사위점수를 사용하여 평가되었으며 평균 0.9026의 성능을 달성하였다.

Measurement of neutrons with high efficiency and large acceptance is essential to study the properties of neutron-rich nuclei using the Large Acceptance Multipurpose Spectrometer (LAMPS) at the rare-isotope beam facility, RAON, in Korea. Here, we propose two plastic-scintillator base detectors for the neutron measurement: a bar-type detector for high-energy and a pixel-type detector for low-energy experiments. Intensive R&Ds for the LAMPS neutron detectors have been addressed to achieve the reliable detector performance required for symmetry-energy researches for neutron-rich nuclei in large neutron-proton asymmetry. In this report, we present the conceptual designs for the LAMPS neutron detectors and the test results for two prototype detector modules with a 5-μCi <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">252</sup> Cf and 10-μCi <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sup> Co sources.

Measurement of isolated photon gives a possibility to constrain the nuclear parton distribution functions (nPDF). The isolated photon is also the clear tag in the photon-jet channel for studying in-medium modifications of fragmentation functions of parton initiated jets. The performance of isolated photon reconstruction and identification has been studied in PbPb collisions at √SNN = 5.02 TeV. Trigger, reconstruction and isolation efficiencies are measured in PYTHIA+HYDJET Monte-Carlo simulation. We describe signal template method to determine the purity of isolated photons.

Dijet measurements in pPb collisions have been shown to be one of the most important tools for constraining the gluon nuclear parton distribution functions (nPDFs) at large Bjorken-x. The dijet pseudorapidity distributions are measured as a function of dijet average transverse momentum in order to study the nuclear modifications of PDFs at various factorization scales. The final results from pp and pPb data samples are compared with next-to-leading-order perturbative QCD predictions obtained from both nucleon and nuclear PDFs. In this paper, we show the latest constraints on nPDFs from studies of dijet pseudorapidity distributions in pp and pPb with the CMS detector.

We propose a method to transmit compresses image files for wireless multimedia services based on FLEX. In a conventional paging system, traffic congestion and delay are serious problems in transmitting large binary files. To overcome these problems, we propose to use a JPEG optimizer to reduce the file size within 4 kbytes and divide a file into a number of small size files. In addition, we assign 4 reserved bits in the header of the message codeword as the divided file number which are used for reassembling divided files into the original binary file. We verify the quality of the transmitted image files by simulation. The results tell us that the proposed method can be operated well under the required BER=10/sup -3/ which is the typical value for wireless communication services.

High-transverse-momentum prompt photons, as colorless objects, do not interact strongly with the medium and provide a direct way to test perturbative QCD and the nuclear parton distribution functions (nPDFs). The transverse energy spectra and the nuclear modification factors of isolated photons are measured in pp and PbPb collisions at sNN=5.02TeV using the CMS detector. The data are compared to jetphox next-to-leading-order calculations and found to be consistent with the prediction of the nuclear modification factor. The measurements significantly improved the accuracy compared to the previous CMS results at sNN=2.76TeV. No significant modification of isolated photon cross-sections in PbPb collisions with respect to pp collisions is observed in the pseudorapidity range |η| < 1.44 for EγT between 25 and 200 GeV at various collision centrality intervals.

The alternating magnetic field shielding efficiency of a YBCO tube was measured in a static field of up to 1 kG, bearing the possibility of its application as a field regulator in mind. The shielding efficiency is higher when the sample is field-cooled than when it is zero-field-cooled, as predicted by the critical state model. In the case of field cooling, the tube still shields about 25% of ac field of 1 kHz even in 500 G dc field. Shielding efficiency monotonously increases with increasing frequency from 10 Hz to 1 kHz.