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Article ; Online: Correction to: Increased Urination Urgency Exacerbates Sexual Risk-Taking Through Heightened Sexual Arousal.

Lee, Juwon / Gillath, Omri

2023 Volume 52, Issue 3, Page(s) 1353

Language	English
Publishing date	2023-03-15
Publishing country	United States
Document type	Published Erratum
ZDB-ID	184221-3
ISSN	1573-2800 ; 0004-0002
ISSN (online)	1573-2800
ISSN	0004-0002
DOI	10.1007/s10508-023-02581-y
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Article ; Online: Increased Urination Urgency Exacerbates Sexual Risk-Taking Through Heightened Sexual Arousal.

Lee, Juwon / Gillath, Omri

Archives of sexual behavior

2022 Volume 51, Issue 6, Page(s) 2955–2967

Abstract: Increased urination urgency has been shown to facilitate impulse control in cognitive domains, but its effects in other areas are unknown. We examined whether inhibitory spillover effects would replicate and extend to close relationships-specifically, ... ...

Abstract	Increased urination urgency has been shown to facilitate impulse control in cognitive domains, but its effects in other areas are unknown. We examined whether inhibitory spillover effects would replicate and extend to close relationships-specifically, influencing decision making related to sexual risk-taking. Across three studies, we either measured (Studies 1 and 3) or manipulated (Study 2) participants' bladder pressure and assessed sexual self-control using a questionnaire of sexual risk-taking intentions (Study 1) or a simulated semi-behavioral sexual risk-taking (Choose Your Own Sexual Adventure) task (Studies 2 and 3). Study 1 (N = 44 men, 59 women) showed greater urination urgency was associated with greater sexual risk-taking. Study 2 (N = 65 men, 91 women) showed that increasing urination urgency led to greater sexual risk-taking, but only among men. Study 3 (N = 86 men, 183 women) showed elevated urination urgency was associated with an increase in sexual arousal, which accounted for the greater sexual risk-taking.
MeSH term(s)	Female ; Humans ; Intention ; Male ; Risk-Taking ; Sexual Arousal ; Sexual Behavior/psychology ; Urinary Incontinence, Urge ; Urination
Language	English
Publishing date	2022-07-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	184221-3
ISSN	1573-2800 ; 0004-0002
ISSN (online)	1573-2800
ISSN	0004-0002
DOI	10.1007/s10508-022-02326-3
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Article ; Online: Numerical study on particle behavior in a Y-junction mixer for supercritical water hydrolysis.

Uruno, Yumi / Lee, Juwon / Jeong, Hanseob / Chung, Jaewon

Bioresource technology

2023 Volume 393, Page(s) 130072

Abstract: In the continuous-type supercritical water hydrolysis process, rapid mixing of supercritical and subcritical streams is important to maximize yield and minimize degradation from over-reaction. This work investigated the particle behavior in a Y-junction ... ...

Abstract	In the continuous-type supercritical water hydrolysis process, rapid mixing of supercritical and subcritical streams is important to maximize yield and minimize degradation from over-reaction. This work investigated the particle behavior in a Y-junction mixer using large eddy simulation coupled with a discrete phase model, aiming to optimize the supercritical hydrolysis process for biomass conversion. A series of numerical simulations analyzed the influence of the mixer's orientation, flow directions, and flow rates on effective mixing and backflow prevention. The results demonstrated that the most effective mixing occurred in a vertically oriented Y-junction mixer with an upward-directed supercritical water inlet, aligning the momentum direction of natural and forced convection effectively. Consequently, over 80% of particles reached the temperatures close to the mixing temperature of supercritical and subcritical water within the Y-junction mixing zone, indicating enhanced mixing effectiveness and potential for efficient hydrolysis. This configuration also minimized backflow.
MeSH term(s)	Water ; Hydrolysis ; Bioreactors ; Computer Simulation ; Temperature
Chemical Substances	Water (059QF0KO0R)
Language	English
Publishing date	2023-11-23
Publishing country	England
Document type	Journal Article
ZDB-ID	1065195-0
ISSN	1873-2976 ; 0960-8524
ISSN (online)	1873-2976
ISSN	0960-8524
DOI	10.1016/j.biortech.2023.130072
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Article ; Online: Smartphone Sensor-Based Human Motion Characterization with Neural Stochastic Differential Equations and Transformer Model.

Lee, Juwon / Kim, Taehwan / Park, Jeongho / Park, Jooyoung

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 19

Abstract: With many conveniences afforded by advances in smartphone technology, developing advanced data analysis methods for health-related information from smartphone users has become a fast-growing research topic in the healthcare field. Along these lines, this ...

Abstract	With many conveniences afforded by advances in smartphone technology, developing advanced data analysis methods for health-related information from smartphone users has become a fast-growing research topic in the healthcare field. Along these lines, this paper addresses smartphone sensor-based characterization of human motions with neural stochastic differential equations (NSDEs) and a Transformer model. NSDEs and modeling via Transformer networks are two of the most prominent deep learning-based modeling approaches, with significant performance yields in many applications. For the problem of modeling dynamical features, stochastic differential equations and deep neural networks are frequently used paradigms in science and engineering, respectively. Combining these two paradigms in one unified framework has drawn significant interest in the deep learning community, and NSDEs are among the leading technologies for combining these efforts. The use of attention has also become a widely adopted strategy in many deep learning applications, and a Transformer is a deep learning model that uses the mechanism of self-attention. This concept of a self-attention based Transformer was originally introduced for tasks of natural language processing (NLP), and due to its excellent performance and versatility, the scope of its applications is rapidly expanding. By utilizing the techniques of neural stochastic differential equations and a Transformer model along with data obtained from smartphone sensors, we present a deep learning method capable of efficiently characterizing human motions. For characterizing human motions, we encode the high-dimensional sequential data from smartphone sensors into latent variables in a low-dimensional latent space. The concept of the latent variable is particularly useful because it can not only carry condensed information concerning motion data, but also learn their low-dimensional representations. More precisely, we use neural stochastic differential equations for modeling transitions of human motion in a latent space, and rely on a Generative Pre-trained Transformer 2 (GPT2)-based Transformer model for approximating the intractable posterior of conditional latent variables. Our experiments show that the proposed method can yield promising results for the problem of characterizing human motion patterns and some related tasks including user identification.
MeSH term(s)	Electric Power Supplies ; Humans ; Motion ; Natural Language Processing ; Neural Networks, Computer ; Smartphone
Language	English
Publishing date	2022-10-02
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22197480
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Article ; Online: Predicting Human Motion Signals Using Modern Deep Learning Techniques and Smartphone Sensors.

Kim, Taehwan / Park, Jeongho / Lee, Juwon / Park, Jooyoung

Sensors (Basel, Switzerland)

2021 Volume 21, Issue 24

Abstract: The global adoption of smartphone technology affords many conveniences, and not surprisingly, healthcare applications using wearable sensors like smartphones have received much attention. Among the various potential applications and research related to ... ...

Abstract	The global adoption of smartphone technology affords many conveniences, and not surprisingly, healthcare applications using wearable sensors like smartphones have received much attention. Among the various potential applications and research related to healthcare, recent studies have been conducted on recognizing human activities and characterizing human motions, often with wearable sensors, and with sensor signals that generally operate in the form of time series. In most studies, these sensor signals are used after pre-processing, e.g., by converting them into an image format rather than directly using the sensor signals themselves. Several methods have been used for converting time series data to image formats, such as spectrograms, raw plots, and recurrence plots. In this paper, we deal with the health care task of predicting human motion signals obtained from sensors attached to persons. We convert the motion signals into image formats with the recurrence plot method, and use it as an input into a deep learning model. For predicting subsequent motion signals, we utilize a recently introduced deep learning model combining neural networks and the Fourier transform, the Fourier neural operator. The model can be viewed as a Fourier-transform-based extension of a convolution neural network, and in these experiments, we compare the results of the model to the convolution neural network (CNN) model. The results of the proposed method in this paper show better performance than the results of the CNN model and, furthermore, we confirm that it can be utilized for detecting potential accidental falls more quickly via predicted motion signals.
MeSH term(s)	Deep Learning ; Human Activities ; Humans ; Motion ; Neural Networks, Computer ; Smartphone
Language	English
Publishing date	2021-12-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s21248270
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Article ; Online: Enhanced Photoresponse of High Crystalline Bi

Cho, Hak Dong / Lee, Juwon / Kim, Deuk Young / Chung, Sung Yun / Lee, Jong-Kwon

ACS applied materials & interfaces

2023 Volume 15, Issue 18, Page(s) 22274–22281

Abstract: High-quality ... ...

Abstract	High-quality Bi
Language	English
Publishing date	2023-04-28
Publishing country	United States
Document type	Journal Article
ISSN	1944-8252
ISSN (online)	1944-8252
DOI	10.1021/acsami.3c02501
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Article ; Online: Fluorescence excitation-emission matrix spectroscopy coupled with parallel factor analysis to determine chlorine decay constants in urban water distribution system.

Lee, Juwon / Nam, Sook-Hyun / Koo, Jae-Wuk / Shin, Yonghyun / Kim, Eunju / Hwang, Tae-Mun

Chemosphere

2023 Volume 331, Page(s) 138733

Abstract: This study applied a method for estimating chlorine decay constant (k) in urban water distribution systems using fluorescence excitation-emission matrix spectroscopy-parallel factor analysis (FEEM-PARAFAC), considering that it accounts for the influence ... ...

Abstract	This study applied a method for estimating chlorine decay constant (k) in urban water distribution systems using fluorescence excitation-emission matrix spectroscopy-parallel factor analysis (FEEM-PARAFAC), considering that it accounts for the influence of organic matter in the target area. The simultaneous impacts of seasonal variations on chlorine consumption and dissolved organic matter (DOM) composition were investigated for a year in three full-scale water distribution systems in I city (areas S, K, and G). Bulk decay constants (kb) were obtained through bottle tests, and the kb value was observed to differ by season and significantly affected by temperature. It exhibited its highest value, 0.794 d
MeSH term(s)	Water ; Chlorine ; Humic Substances/analysis ; Spectrometry, Fluorescence/methods ; Halogens ; Factor Analysis, Statistical
Chemical Substances	Water (059QF0KO0R) ; Chlorine (4R7X1O2820) ; Humic Substances ; Halogens
Language	English
Publishing date	2023-04-25
Publishing country	England
Document type	Journal Article
ZDB-ID	120089-6
ISSN	1879-1298 ; 0045-6535 ; 0366-7111
ISSN (online)	1879-1298
ISSN	0045-6535 ; 0366-7111
DOI	10.1016/j.chemosphere.2023.138733
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Article ; Online: Electronic tongue for the simple and rapid determination of taste and odor compounds in water.

Nam, Sook-Hyun / Lee, Juwon / Kim, Eunju / Koo, Jae-Wuk / Shin, Yonghyun / Hwang, Tae-Mun

Chemosphere

2023 Volume 338, Page(s) 139511

Abstract: Taste and odor (T&O) compounds present in natural water bodies could originate from algae. In this study, alga-generated compounds that can cause T&O issues in water, such as geosmin (GE), 2-Methylisoborneol (MIB), 2,4,6-Trichloroanisole (TCA), 2- ... ...

Abstract	Taste and odor (T&O) compounds present in natural water bodies could originate from algae. In this study, alga-generated compounds that can cause T&O issues in water, such as geosmin (GE), 2-Methylisoborneol (MIB), 2,4,6-Trichloroanisole (TCA), 2-Methylbenzofuran (MB), 2-Isopropyl-3-methoxypyrazine (IPMP), 2-Isobutyl-3-methoxypyrazine (IBMP), cis-3-Hexenyl acetate (HA), trans,trans-2,4-Heptadienal (HD), trans,cis-2,6-Nonadienal (ND), and trans-2-Decenal (DN), were determined through solid-phase microextraction coupled with gas chromatography/mass spectrometry (HS-SPME GC/MS) and electronic tongue (E-tongue), and the results from the two techniques were compared. Although HS-SPME GC/MS facilitates the detection and quantification of T&O compounds with high precision and accuracy, the sample preparation and handling is difficult and the analysis time (1 h) is longer than those of other analytical methods. E-tongue can be used as an alternative analytical method for water quality analysis and risk management because it enables controlled and rapid analysis (3 min) of T&O compounds in water at a low cost. Notably, principal component analysis indicated that E-tongue can discriminate and quantify eight T&O compounds at as low as 0.02 μg L
MeSH term(s)	Odorants/analysis ; Taste ; Electronic Nose ; Gas Chromatography-Mass Spectrometry/methods
Chemical Substances	geosmin (MYW912WXJ4)
Language	English
Publishing date	2023-07-19
Publishing country	England
Document type	Journal Article
ZDB-ID	120089-6
ISSN	1879-1298 ; 0045-6535 ; 0366-7111
ISSN (online)	1879-1298
ISSN	0045-6535 ; 0366-7111
DOI	10.1016/j.chemosphere.2023.139511
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Article ; Online: Mitochondrial fission enhances IL-6-induced metastatic potential in ovarian cancer via ERK1/2 activation.

Lee, Juwon / Han, Youngjin / Kim, Soochi / Jo, HyunA / Wang, Wenyu / Cho, Untack / Kim, Se Ik / Kim, Boyun / Song, Yong Sang

Cancer science

2024 Volume 115, Issue 5, Page(s) 1536–1550

Abstract: Ovarian cancer is a lethal gynecologic cancer mostly diagnosed in an advanced stage with an accumulation of ascites. Interleukin-6 (IL-6), a pro-inflammatory cytokine is highly elevated in malignant ascites and plays a pleiotropic role in cancer ... ...

Abstract	Ovarian cancer is a lethal gynecologic cancer mostly diagnosed in an advanced stage with an accumulation of ascites. Interleukin-6 (IL-6), a pro-inflammatory cytokine is highly elevated in malignant ascites and plays a pleiotropic role in cancer progression. Mitochondria are dynamic organelles that undergo fission and fusion in response to external stimuli and dysregulation in their dynamics has been implicated in cancer progression and metastasis. Here, we investigate the effect of IL-6 on mitochondrial dynamics in ovarian cancer cells (OVCs) and its impact on metastatic potential. Treatment with IL-6 on ovarian cancer cell lines (SKOV3 and PA-1) led to an elevation in the metastatic potential of OVCs. Interestingly, a positive association was observed between dynamin-related protein 1 (Drp1), a regulator of mitochondrial fission, and IL-6R in metastatic ovarian cancer tissues. Additionally, IL-6 treatment on OVCs was linked to the activation of Drp1, with a notable increase in the ratio of the inhibitory form p-Drp1(S637) to the active form p-Drp1(S616), indicating enhanced mitochondrial fission. Moreover, IL-6 treatment triggered the activation of ERK1/2, and inhibiting ERK1/2 mitigated IL-6-induced mitochondrial fission. Suppressing mitochondrial fission through siRNA transfection and a pharmacological inhibitor reduced the IL-6-induced migration and invasion of OVCs. This was further supported by 3D invasion assays using patient-derived spheroids. Altogether, our study suggests the role of mitochondrial fission in the metastatic potential of OVCs induced by IL-6. The inhibition of mitochondrial fission could be a potential therapeutic approach to suppress the metastasis of ovarian cancer.
MeSH term(s)	Humans ; Female ; Mitochondrial Dynamics/drug effects ; Ovarian Neoplasms/pathology ; Ovarian Neoplasms/metabolism ; Interleukin-6/metabolism ; Dynamins/metabolism ; Cell Line, Tumor ; MAP Kinase Signaling System/drug effects ; Neoplasm Metastasis ; Mitochondria/metabolism ; Receptors, Interleukin-6/metabolism ; Cell Movement/drug effects
Language	English
Publishing date	2024-03-03
Publishing country	England
Document type	Journal Article
ZDB-ID	2115647-5
ISSN	1349-7006 ; 1349-7006
ISSN (online)	1349-7006
ISSN	1349-7006
DOI	10.1111/cas.16064
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Article ; Online: Electronic tongue for the simple and rapid determination of taste and odor compounds in water

Nam, Sook-Hyun / Lee, Juwon / Kim, Eunju / Koo, Jae-Wuk / Shin, Yonghyun / Hwang, Tae-Mun

Chemosphere. 2023 Oct., v. 338 p.139511-

2023

Abstract	Taste and odor (T&O) compounds present in natural water bodies could originate from algae. In this study, alga-generated compounds that can cause T&O issues in water, such as geosmin (GE), 2-Methylisoborneol (MIB), 2,4,6-Trichloroanisole (TCA), 2-Methylbenzofuran (MB), 2-Isopropyl-3-methoxypyrazine (IPMP), 2-Isobutyl-3-methoxypyrazine (IBMP), cis-3-Hexenyl acetate (HA), trans,trans-2,4-Heptadienal (HD), trans,cis-2,6-Nonadienal (ND), and trans-2-Decenal (DN), were determined through solid-phase microextraction coupled with gas chromatography/mass spectrometry (HS-SPME GC/MS) and electronic tongue (E-tongue), and the results from the two techniques were compared. Although HS-SPME GC/MS facilitates the detection and quantification of T&O compounds with high precision and accuracy, the sample preparation and handling is difficult and the analysis time (1 h) is longer than those of other analytical methods. E-tongue can be used as an alternative analytical method for water quality analysis and risk management because it enables controlled and rapid analysis (3 min) of T&O compounds in water at a low cost. Notably, principal component analysis indicated that E-tongue can discriminate and quantify eight T&O compounds at as low as 0.02 μg L⁻¹ concentration. Further, partial least squares analysis confirmed that the sensor exhibits high sensitivity to concentration changes. The sensors with the highest variable importance in projection scores were determined to be SCS (1.39 and 1.38) for GE and MIB, CTS (1.34) for IPMP, CPS (1.33) for IBMP, AHS (1.42) for HA, ANS (1.22) for HD, and NMS (1.14 and 1.19) for ND and DN.
Keywords	2-methylisoborneol ; acetates ; electronic tongue ; gas chromatography ; geosmin ; mass spectrometry ; odors ; principal component analysis ; rapid methods ; risk management ; solid phase microextraction ; taste ; water quality analysis ; Multivariate analysis ; Rapid water monitoring ; Taste and odor compounds
Language	English
Dates of publication	2023-10
Publishing place	Elsevier Ltd
Document type	Article ; Online
Note	Pre-press version
ZDB-ID	120089-6
ISSN	1879-1298 ; 0045-6535 ; 0366-7111
ISSN (online)	1879-1298
ISSN	0045-6535 ; 0366-7111
DOI	10.1016/j.chemosphere.2023.139511
Database	NAL-Catalogue (AGRICOLA)

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