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Authors = Junghyun Kim

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19 pages, 1025 KiB  
Review
A Genetically-Informed Network Model of Myelodysplastic Syndrome: From Splicing Aberrations to Therapeutic Vulnerabilities
by Sanghyeon Yu, Junghyun Kim and Man S. Kim
Genes 2025, 16(8), 928; https://doi.org/10.3390/genes16080928 (registering DOI) - 1 Aug 2025
Viewed by 177
Abstract
Background/Objectives: Myelodysplastic syndrome (MDS) is a heterogeneous clonal hematopoietic disorder characterized by ineffective hematopoiesis and leukemic transformation risk. Current therapies show limited efficacy, with ~50% of patients failing hypomethylating agents. This review aims to synthesize recent discoveries through an integrated network model [...] Read more.
Background/Objectives: Myelodysplastic syndrome (MDS) is a heterogeneous clonal hematopoietic disorder characterized by ineffective hematopoiesis and leukemic transformation risk. Current therapies show limited efficacy, with ~50% of patients failing hypomethylating agents. This review aims to synthesize recent discoveries through an integrated network model and examine translation into precision therapeutic approaches. Methods: We reviewed breakthrough discoveries from the past three years, analyzing single-cell multi-omics technologies, epitranscriptomics, stem cell architecture analysis, and precision medicine approaches. We examined cell-type-specific splicing aberrations, distinct stem cell architectures, epitranscriptomic modifications, and microenvironmental alterations in MDS pathogenesis. Results: Four interconnected mechanisms drive MDS: genetic alterations (splicing factor mutations), aberrant stem cell architecture (CMP-pattern vs. GMP-pattern), epitranscriptomic dysregulation involving pseudouridine-modified tRNA-derived fragments, and microenvironmental changes. Splicing aberrations show cell-type specificity, with SF3B1 mutations preferentially affecting erythroid lineages. Stem cell architectures predict therapeutic responses, with CMP-pattern MDS achieving superior venetoclax response rates (>70%) versus GMP-pattern MDS (<30%). Epitranscriptomic alterations provide independent prognostic information, while microenvironmental changes mediate treatment resistance. Conclusions: These advances represent a paradigm shift toward personalized MDS medicine, moving from single-biomarker to comprehensive molecular profiling guiding multi-target strategies. While challenges remain in standardizing molecular profiling and developing clinical decision algorithms, this systems-level understanding provides a foundation for precision oncology implementation and overcoming current therapeutic limitations. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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21 pages, 1057 KiB  
Article
Hybrid Sensor Placement Framework Using Criterion-Guided Candidate Selection and Optimization
by Se-Hee Kim, JungHyun Kyung, Jae-Hyoung An and Hee-Chang Eun
Sensors 2025, 25(14), 4513; https://doi.org/10.3390/s25144513 - 21 Jul 2025
Viewed by 256
Abstract
This study presents a hybrid sensor placement methodology that combines criterion-based candidate selection with advanced optimization algorithms. Four established selection criteria—modal kinetic energy (MKE), modal strain energy (MSE), modal assurance criterion (MAC) sensitivity, and mutual information (MI)—are used to evaluate DOF sensitivity and [...] Read more.
This study presents a hybrid sensor placement methodology that combines criterion-based candidate selection with advanced optimization algorithms. Four established selection criteria—modal kinetic energy (MKE), modal strain energy (MSE), modal assurance criterion (MAC) sensitivity, and mutual information (MI)—are used to evaluate DOF sensitivity and generate candidate pools. These are followed by one of four optimization algorithms—greedy, genetic algorithm (GA), particle swarm optimization (PSO), or simulated annealing (SA)—to identify the optimal subset of sensor locations. A key feature of the proposed approach is the incorporation of constraint dynamics using the Udwadia–Kalaba (U–K) generalized inverse formulation, which enables the accurate expansion of structural responses from sparse sensor data. The framework assumes a noise-free environment during the initial sensor design phase, but robustness is verified through extensive Monte Carlo simulations under multiple noise levels in a numerical experiment. This combined methodology offers an effective and flexible solution for data-driven sensor deployment in structural health monitoring. To clarify the rationale for using the Udwadia–Kalaba (U–K) generalized inverse, we note that unlike conventional pseudo-inverses, the U–K method incorporates physical constraints derived from partial mode shapes. This allows a more accurate and physically consistent reconstruction of unmeasured responses, particularly under sparse sensing. To clarify the benefit of using the U–K generalized inverse over conventional pseudo-inverses, we emphasize that the U–K method allows the incorporation of physical constraints derived from partial mode shapes directly into the reconstruction process. This leads to a constrained dynamic solution that not only reflects the known structural behavior but also improves numerical conditioning, particularly in underdetermined or ill-posed cases. Unlike conventional Moore–Penrose pseudo-inverses, which yield purely algebraic solutions without physical insight, the U–K formulation ensures that reconstructed responses adhere to dynamic compatibility, thereby reducing artifacts caused by sparse measurements or noise. Compared to unconstrained least-squares solutions, the U–K approach improves stability and interpretability in practical SHM scenarios. Full article
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13 pages, 1527 KiB  
Article
Ethnic-Specific and UV-Independent Mutational Signatures of Basal Cell Carcinoma in Koreans
by Ye-Ah Kim, Seokho Myung, Yueun Choi, Junghyun Kim, Yoonsung Lee, Kiwon Lee, Bark-Lynn Lew, Man S. Kim and Soon-Hyo Kwon
Int. J. Mol. Sci. 2025, 26(14), 6941; https://doi.org/10.3390/ijms26146941 - 19 Jul 2025
Viewed by 333
Abstract
Basal cell carcinoma (BCC), the most common skin cancer, is primarily driven by Hedgehog (Hh) and TP53 pathway alterations. Although additional pathways were implicated, the mutational landscape in Asian populations, particularly Koreans, remains underexplored. We performed whole-exome sequencing of BCC tumor tissues from [...] Read more.
Basal cell carcinoma (BCC), the most common skin cancer, is primarily driven by Hedgehog (Hh) and TP53 pathway alterations. Although additional pathways were implicated, the mutational landscape in Asian populations, particularly Koreans, remains underexplored. We performed whole-exome sequencing of BCC tumor tissues from Korean patients and analyzed mutations in 11 established BCC driver genes (PTCH1, SMO, GLI1, TP53, CSMD1/2, NOTCH1/2, ITIH2, DPP10, and STEAP4). Mutational profiles were compared with Caucasian cohort profiles to identify ethnicity-specific variants. Ultraviolet (UV)-exposed and non-UV-exposed tumor sites were compared; genes unique to non-UV-exposed tumors were further analyzed with protein–protein interaction analysis. BCCs in Koreans exhibited distinct features, including fewer truncating and more intronic variants compared to Caucasians. Korean-specific mutations in SMO, PTCH1, TP53, and NOTCH2 overlapped with oncogenic gain-of-function/loss-of-function (GOF/LOF) variants annotated in OncoKB, with some occurring at hotspot sites. BCCs in non-exposed areas showed recurrent mutations in CSMD1, PTCH1, and NOTCH1, suggesting a UV-independent mechanism. Novel mutations in TAS1R2 and ADCY10 were exclusive to non-exposed BCCs, with protein–protein interaction analysis linking them to TP53 and NOTCH2. We found unique ethnic-specific and UV-independent mutational profiles of BCCs in Koreans. TAS1R2 and ADCY10 may contribute to tumorigenesis of BCC in non-exposed areas, supporting the need for population-specific precision oncology. Full article
(This article belongs to the Special Issue Skin Cancer: From Molecular Pathophysiology to Novel Treatment)
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15 pages, 5686 KiB  
Article
High-Order Model-Based Robust Control of a Dual-Motor Steer-by-Wire System with Disturbance Rejection
by Minhyung Kim, Insu Chung, Junghyun Choi and Kanghyun Nam
Actuators 2025, 14(7), 322; https://doi.org/10.3390/act14070322 - 30 Jun 2025
Viewed by 309
Abstract
This paper presents a high-order model-based robust control strategy for a dual-motor road wheel actuating system in a steer-by-wire (SbW) architecture. The system consists of a belt-driven and a pinion-driven motor collaboratively actuating the road wheels through mechanically coupled dynamics. To accurately capture [...] Read more.
This paper presents a high-order model-based robust control strategy for a dual-motor road wheel actuating system in a steer-by-wire (SbW) architecture. The system consists of a belt-driven and a pinion-driven motor collaboratively actuating the road wheels through mechanically coupled dynamics. To accurately capture the interaction between actuators, structural compliance, and road disturbances, a four-degree-of-freedom (4DOF) lumped-parameter model is developed. Leveraging this high-order dynamic model, a composite control framework is proposed, integrating feedforward model inversion, pole-zero feedback compensation, and a disturbance observer (DOB) to ensure precise trajectory tracking and disturbance rejection. High-fidelity co-simulations in MATLAB/Simulink and Siemens Amesim validate the effectiveness of the proposed control under various steering scenarios, including step and sine-sweep inputs. Compared to conventional low-order control methods, the proposed approach significantly reduces tracking error and demonstrates enhanced robustness and disturbance attenuation. These results highlight the critical role of high-order modeling in the precision control of dual-motor SbW systems and suggest its applicability in real-time, safety-critical vehicle steering applications. Full article
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17 pages, 2850 KiB  
Article
Influence of NaCl on Phase Development and Corrosion Resistance of Portland Cement
by Byung-Hyun Shin, Miyoung You, Jinyong Park, Junghyun Cho, Seongjun Kim, Jung-Woo Ok, Jonggi Hong, Taekyu Lee, Jong-Seong Bae, Pungkeun Song and Jang-Hee Yoon
Crystals 2025, 15(6), 579; https://doi.org/10.3390/cryst15060579 - 19 Jun 2025
Viewed by 365
Abstract
Portland cement is one of the most widely used construction materials employed in both large-scale structures and everyday applications. Although various materials are often added during production to enhance their performance, NaCl can be introduced in the process for various reasons. Despite this [...] Read more.
Portland cement is one of the most widely used construction materials employed in both large-scale structures and everyday applications. Although various materials are often added during production to enhance their performance, NaCl can be introduced in the process for various reasons. Despite this issue, existing studies lack sufficient quantitative data on the effects of NaCl on cement properties. Therefore, this study aims to investigate the physical and chemical degradation mechanisms in cement containing NaCl. Cement specimens were prepared by mixing cement, water, and NaCl, followed by stirring at 60 rpm and curing at room temperature for seven days. Microstructural changes as a function of the NaCl concentration were analyzed using scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Electrochemical properties were evaluated via open-circuit potential (OCP) measurements, electrochemical impedance spectroscopy (EIS), and potentiodynamic polarization tests. The results indicate that increasing the NaCl concentration leads to the formation of fine precipitates, the degradation of the cement matrix, and the reduced stability of major hydration products. Furthermore, the electrochemical analysis revealed that higher NaCl concentrations weaken the passive layer on the cement surface, resulting in an increased corrosion rate from 1 × 10−7 to 4 × 10−7 on the active polarization of the potentiodynamic polarization curve. Additionally, the pitting potential (Epit) decreased from 0.73 V to 0.61 V with an increasing NaCl concentration up to 3 wt.%. This study quantitatively evaluates the impact of NaCl on the durability of Portland cement and provides fundamental data to ensure the long-term stability of cement structures in chloride-rich environments. Full article
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12 pages, 237 KiB  
Article
Determination of Digestible Indispensable Amino Acid Scores for Plant Proteins and Skim Milk Powder Measured in Pigs
by Junghyun Oh, Noa Park and Beob Gyun Kim
Animals 2025, 15(5), 650; https://doi.org/10.3390/ani15050650 - 24 Feb 2025
Cited by 1 | Viewed by 1140
Abstract
The objective was to determine the digestible indispensable amino acid score (DIAAS) of food sources using the pig model and in vitro procedures. The standardized ileal digestibility (SID) of amino acids (AA) in white rice, wheat, pea protein concentrate (PPC), soy protein isolate [...] Read more.
The objective was to determine the digestible indispensable amino acid score (DIAAS) of food sources using the pig model and in vitro procedures. The standardized ileal digestibility (SID) of amino acids (AA) in white rice, wheat, pea protein concentrate (PPC), soy protein isolate (SPI), and skim milk powder (SMP) were determined in pigs. Twelve barrows with an initial body weight of 28.4 kg (standard deviation = 4.0) equipped with a T-cannula at the distal ileum were allotted to a replicated 6 × 5 incomplete Latin square design with six diets and five periods. Five experimental diets contained each ingredient as the only source of AA. Additionally, a nitrogen-free diet was prepared to measure the basal endogenous losses of AA for the calculation of the SID of AA. The in vitro ileal disappearance (IVID) of crude protein (CP) in the five food sources was also determined using the conventional flask procedure and the multi-sample simultaneous in vitro procedure employing the DaisyII incubator. The DIAAS values for white rice were 42, 50, and 60 for infants, children, and adults, respectively. For wheat, the DIAAS values were 46, 56, and 66, respectively. The DIAAS values for PPC were 47, 58, and 69 for infants, children, and adults, respectively. For SPI, the values were 61, 74, and 87, respectively. The DIAAS for SMP were 82, 112, and 131 for infants, children, and adults respectively. The IVID of CP in SMP was greater (p < 0.05) than that in other sources. The DIAAS calculated based on IVID of CP were similar to those determined based on the SID of AA in pigs. In conclusion, white rice, wheat, pea protein concentrate, and soy protein isolate were observed to have DIAAS values less than 100, indicating that these ingredients need to be combined with other protein sources to meet the indispensable AA requirements. Skim milk powder had a DIAAS greater than 100 for children and adults. Full article
(This article belongs to the Section Pigs)
18 pages, 5240 KiB  
Article
Assessing the Efficacy of Mitochondria-Accumulating Self-Assembly Peptides in Pancreatic Cancer: An Animal Study
by Ho Joong Choi, Seongeon Jin, Junghyun Park, Dosang Lee, Hee Jeong Jeong, Ok-Hee Kim, Ja-Hyoung Ryu and Say-June Kim
Int. J. Mol. Sci. 2025, 26(2), 784; https://doi.org/10.3390/ijms26020784 - 17 Jan 2025
Viewed by 1215
Abstract
Although pancreatic cancer presents with one of the most unfavorable prognoses, its treatment options are very limited. Mitochondria-targeting moieties, considered a new and prominent treatment modality, are expected to demonstrate synergistic anticancer effects due to their distinct mechanism compared to conventional chemotherapeutic approaches. [...] Read more.
Although pancreatic cancer presents with one of the most unfavorable prognoses, its treatment options are very limited. Mitochondria-targeting moieties, considered a new and prominent treatment modality, are expected to demonstrate synergistic anticancer effects due to their distinct mechanism compared to conventional chemotherapeutic approaches. This study evaluated the therapeutic potential of mitochondria-accumulating self-assembly peptides, referred to as Mito-FFs, utilizing both in vitro and in vivo pancreatic cancer models. Cellular viability assays revealed a concentration-dependent decrease in the survival of MIA-PACA2 pancreatic cancer cells upon exposure to Mito-FF treatment (p < 0.05). Subsequent in vitro Mito-FF treatments prompted the use of several molecular analyses, including Real-time PCR, Western blot analysis, and MitoSOX staining, which collectively indicated an upsurge in apoptosis, a concurrent reduction in the antioxidant enzyme expression, and an elevation in mitochondrial ROS levels (p < 0.05). In a murine xenograft model of pancreatic cancer, the intravenous administration of Mito-FF yielded a notable reduction in the tumor volume. Moreover, it upregulated the expression of pro-apoptotic markers, such as cleaved PARP and c-caspase 3, while concurrently downregulating the expression of an anti-apoptotic marker, MCL-1, as evidenced by both Western blot analysis and immunohistochemical staining (p < 0.05). It also resulted in the reduced expression of antioxidant enzymes like HO-1, catalase, and SOD2 within excised tumor tissues, as confirmed using Western blot analysis (p < 0.05). Cumulatively, the findings underscore the significant anticancer efficacy of Mito-FF against pancreatic cancer cells, predominantly mediated through the induction of apoptosis, suppression of antioxidant enzyme expression, and enhancement of mitochondrial ROS levels within the tumor microenvironment. Full article
(This article belongs to the Special Issue Mitochondrial Function in Health and Diseases)
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18 pages, 6983 KiB  
Article
Multiscale Convolution-Based Efficient Channel Estimation Techniques for OFDM Systems
by Nahyeon Kwon, Bora Yoon and Junghyun Kim
Electronics 2025, 14(2), 307; https://doi.org/10.3390/electronics14020307 - 14 Jan 2025
Viewed by 1078
Abstract
With the advancement of wireless communication technology, the significance of efficient and accurate channel estimation methods has grown substantially. Recently, deep learning-based methods are being adopted to estimate channels with higher precision than traditional methods, even in the absence of prior channel statistics. [...] Read more.
With the advancement of wireless communication technology, the significance of efficient and accurate channel estimation methods has grown substantially. Recently, deep learning-based methods are being adopted to estimate channels with higher precision than traditional methods, even in the absence of prior channel statistics. In this paper, we propose two deep learning-based channel estimation models, CAMPNet and MSResNet, which are designed to consider channel characteristics from a multiscale perspective. The convolutional attention and multiscale parallel network (CAMPNet) accentuates critical channel characteristics by utilizing parallel multiscale features and convolutional attention, while the multiscale residual network (MSResNet) integrates information across various scales through cross-connected multiscale convolutional structures. Both models are designed to perform robustly in environments with complex frequency domain information and various Doppler shifts. Experimental results demonstrate that CAMPNet and MSResNet achieve superior performance compared to existing channel estimation methods within various channel models. Notably, the proposed models show exceptional performance in high signal-to-noise ratio (SNR) environments, achieving up to a 48.98% reduction in mean squared error(MSE) compared to existing methods at an SNR of 25dB. In experiments evaluating the generalization capabilities of the proposed models, they show greater stability and robustness compared to existing methods. These results suggest that deep learning-based channel estimation models have the potential to overcome the limitations of existing methods, offering high performance and efficiency in real-world communication environments. Full article
(This article belongs to the Section Circuit and Signal Processing)
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14 pages, 303 KiB  
Article
Buddhist Discourse in Changing Times: The Significance of Buddhist Magazines in Early 20th-Century Korea with a Focus on Bulgyo
by Junghyun Kwon and Jongjin Kim
Religions 2024, 15(11), 1400; https://doi.org/10.3390/rel15111400 - 18 Nov 2024
Viewed by 1491
Abstract
In early 20th-century Korea, Buddhist magazines emerged as vital extra-canonical sources, offering a modern platform that complemented traditional Buddhist texts. These publications navigated the complexities between succeeding Buddhist tradition and embracing modernity, addressing the historical challenges of the 19th century while also contributing [...] Read more.
In early 20th-century Korea, Buddhist magazines emerged as vital extra-canonical sources, offering a modern platform that complemented traditional Buddhist texts. These publications navigated the complexities between succeeding Buddhist tradition and embracing modernity, addressing the historical challenges of the 19th century while also contributing to the preservation of national sovereignty and the formation of a modern Korean Buddhist identity. Serving as a forum for scholarly works on Buddhist translation, doctrine, and history, as well as literature, education, and propagation, these magazines became central to both intellectual and spiritual discourse. Of the more than 30 periodicals published during the Japanese occupation, Bulgyo stood out as the longest-running and most influential magazine, with its complete archive preserved. Bulgyo brought together various members of the Buddhist community as both contributors and readers, broadening the scope of Buddhism to include a diverse range of topics such as academia, literature, art, women, and children. This article explores the role and significance of Korean Buddhist magazines during the Japanese colonial period, with a particular focus on Bulgyo, and examines how the publication helped shape Buddhist modernity within Korea’s complex political and religious landscape. Full article
16 pages, 491 KiB  
Article
Optimal Community Energy Storage System Operation in a Multi-Power Consumer System: A Stackelberg Game Theory Approach
by Gyeong Ho Lee, Junghyun Lee, Seong Gon Choi and Jangkyum Kim
Energies 2024, 17(22), 5683; https://doi.org/10.3390/en17225683 - 13 Nov 2024
Cited by 1 | Viewed by 1322
Abstract
The proliferation of community energy storage systems (CESSs) necessitates effective energy management to address financial concerns. This paper presents an efficient energy management scheme for heterogeneous power consumers by analyzing various cost factors relevant to the power system. We propose an authority transaction [...] Read more.
The proliferation of community energy storage systems (CESSs) necessitates effective energy management to address financial concerns. This paper presents an efficient energy management scheme for heterogeneous power consumers by analyzing various cost factors relevant to the power system. We propose an authority transaction model based on a multi-leader multi-follower Stackelberg game, demonstrating the existence of a unique Stackelberg equilibrium to determine optimal bidding prices and allocate authority transactions. Our model shows that implementing a CESS can reduce total electricity costs by 16% compared to the conventional case that does not account for authority transactions among CESS users, highlighting its effectiveness in practical power systems. Full article
(This article belongs to the Special Issue State-of-the-Art Machine Learning Tools for Energy Systems)
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8 pages, 602 KiB  
Article
Drying Methods for Black Soldier Fly (Hermetia illucens) Larvae as a Feed Ingredient for Pigs Affect In Vitro Nutrient Disappearance
by Junghyun Oh, Hansol Kim, Kwanho Park and Beob Gyun Kim
Agriculture 2024, 14(10), 1792; https://doi.org/10.3390/agriculture14101792 - 12 Oct 2024
Cited by 2 | Viewed by 3269
Abstract
The objective of the present research was to determine the nutrient utilization of full-fat black soldier fly larvae (Hermetia illucens; BSFL), which were processed by various drying methods, using in vitro procedures for pigs. Four sources of BSFL were prepared using [...] Read more.
The objective of the present research was to determine the nutrient utilization of full-fat black soldier fly larvae (Hermetia illucens; BSFL), which were processed by various drying methods, using in vitro procedures for pigs. Four sources of BSFL were prepared using various drying methods: (1) hot-air drying at 65 °C for 24 h; (2) microwave drying at 700 W for 5 min, three times; (3) freeze drying at −40 °C for 72 h; (4) infrared drying at medium infrared region (ranged from 2.0 to 6.0 μm) and at 95 °C for 12 min. In vitro ileal disappearance (IVID) of nutrients in the BSFL was measured using a procedure simulating the nutrient digestion and absorption in the stomach and small intestine of pigs. In vitro total tract disappearance (IVTTD) of nutrients in the BSFL was also measured using a procedure that simulated the total intestine of pigs. The contents of dry matter, ether extract, and crude protein in the dried-BSFL ranged from 94.6 to 96.8%, 49.2 to 52.8%, and 30.0 to 36.8%, respectively, on an as-is basis. Microwave drying resulted in a greater (p < 0.05) IVID of dry matter in BSFL, compared with the freeze drying or infrared drying method, which caused the least IVID of dry matter. Hot air-dried BSFL, microwave-dried BSFL, and freeze-dried BSFL had a greater (p < 0.05) IVID of crude protein and a greater (p < 0.05) IVTTD of dry matter and organic matter, compared with infrared-dried BSFL. In conclusion, the hot-air drying, microwave drying, and freeze drying of full-fat black soldier fly larvae resulted in fairly comparable and relatively high nutrient digestibility based on the present in vitro study for pigs. However, the infrared drying method impaired nutrient utilization of full-fat black soldier fly larvae for pigs. Full article
(This article belongs to the Section Farm Animal Production)
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20 pages, 2516 KiB  
Article
Rapid PM2.5-Induced Health Impact Assessment: A Novel Approach Using Conditional U-Net CMAQ Surrogate Model
by Yohan Lee, Junghyun Park, Jinseok Kim, Jung-Hun Woo and Jong-Hyeon Lee
Atmosphere 2024, 15(10), 1186; https://doi.org/10.3390/atmos15101186 - 2 Oct 2024
Cited by 2 | Viewed by 1663
Abstract
There is a pressing need for tools that can rapidly predict PM2.5 concentrations and assess health impacts under various emission scenarios, aiding in the selection of optimal mitigation strategies. Traditional chemical transport models (CTMs) like CMAQ are accurate but computationally intensive, limiting [...] Read more.
There is a pressing need for tools that can rapidly predict PM2.5 concentrations and assess health impacts under various emission scenarios, aiding in the selection of optimal mitigation strategies. Traditional chemical transport models (CTMs) like CMAQ are accurate but computationally intensive, limiting practical scenario analysis. To address this, we propose a novel method integrating a conditional U-Net surrogate model with health impact assessments, enabling swift estimation of PM2.5 concentrations and related health effects. The U-Net model was trained with 2019 South Korean PM2.5 data, including precursor emissions and boundary conditions. Our model showed high accuracy and significant efficiency, reducing processing times while maintaining reliability. By combining this surrogate model with the EPA’s BenMAP-CE tool, we estimated potential premature deaths under various emission reduction scenarios in South Korea, extending projections to 2050 to account for demographic changes. Additionally, we assessed the required PM2.5 emission reductions needed to counteract the increase in premature deaths due to an aging population. This integrated framework offers an efficient, user-friendly tool that bridges complex air quality modeling with practical policy evaluation, supporting the development of effective strategies to reduce PM2.5-related health risks and estimate economic benefits. Full article
(This article belongs to the Special Issue Air Pollution: Health Risks and Mitigation Strategies)
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14 pages, 2961 KiB  
Article
Electromyography-Triggered Constraint-Induced Movement Cycling Therapy for Enhancing Motor Function in Chronic Stroke Patients: A Randomized Controlled Trial
by Jaemyoung Park, Kyeongjin Lee, Junghyun Kim and Changho Song
Bioengineering 2024, 11(9), 860; https://doi.org/10.3390/bioengineering11090860 - 23 Aug 2024
Cited by 1 | Viewed by 1469
Abstract
This single-blind randomized controlled trial investigated the effectiveness of surface electromyography (sEMG)-triggered constraint-induced movement cycling therapy (CIMCT) in improving balance, lower extremity strength, and activities of daily living in patients with chronic stroke. The participants included patients with chronic stroke-induced hemiplegia who had [...] Read more.
This single-blind randomized controlled trial investigated the effectiveness of surface electromyography (sEMG)-triggered constraint-induced movement cycling therapy (CIMCT) in improving balance, lower extremity strength, and activities of daily living in patients with chronic stroke. The participants included patients with chronic stroke-induced hemiplegia who had been diagnosed for more than 6 months, with a minimum score of 24 points on the Mini-Mental State Examination and above level 3 on the Brunnstrom stages. The trial lasted 4 weeks and participants were divided into a CIMCT group and a general cycling training (GCT) group. The CIMCT group (n = 20) used an sEMG-triggered constrained-induced movement therapy device, whereas the GCT group (n = 19) used a standard stationary bicycle. The primary outcome measures showed a significant increase in muscle strength on the affected side in the CIMCT group, as assessed by a manual muscle tester (p < 0.05), with a large effect size (d = 1.86), while no meaningful improvement was observed in the GCT group. Both groups demonstrated significant improvements in dynamic balance, as measured by the Timed Up and Go (TUG) test (p < 0.05), with the CIMCT group showing superior results compared to the GCT group, reflected by a large effect size (d = 0.96). Additionally, both groups showed significant improvements in balance as assessed by the Berg Balance Scale (BBS) and the Functional Reach Test (FRT). The CIMCT group exhibited more pronounced improvements than the GCT group, with large effect sizes of 0.83 for the BBS and 1.25 for the FRT. The secondary outcome measures revealed significant improvements in activities of daily living in both groups, as assessed by the modified Barthel index (MBI), with the CIMCT group achieving a substantial improvement (p < 0.05), accompanied by a large effect size (d = 0.87). This study concludes that sEMG-triggered CIMCT effectively improved muscle strength, postural balance, and activities of daily living in patients with chronic stroke. Full article
(This article belongs to the Special Issue Bioengineering of the Motor System)
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14 pages, 1823 KiB  
Article
Adapt-cMolGPT: A Conditional Generative Pre-Trained Transformer with Adapter-Based Fine-Tuning for Target-Specific Molecular Generation
by Soyoung Yoo and Junghyun Kim
Int. J. Mol. Sci. 2024, 25(12), 6641; https://doi.org/10.3390/ijms25126641 - 17 Jun 2024
Viewed by 1663
Abstract
Small-molecule drug design aims to generate compounds that target specific proteins, playing a crucial role in the early stages of drug discovery. Recently, research has emerged that utilizes the GPT model, which has achieved significant success in various fields to generate molecular compounds. [...] Read more.
Small-molecule drug design aims to generate compounds that target specific proteins, playing a crucial role in the early stages of drug discovery. Recently, research has emerged that utilizes the GPT model, which has achieved significant success in various fields to generate molecular compounds. However, due to the persistent challenge of small datasets in the pharmaceutical field, there has been some degradation in the performance of generating target-specific compounds. To address this issue, we propose an enhanced target-specific drug generation model, Adapt-cMolGPT, which modifies molecular representation and optimizes the fine-tuning process. In particular, we introduce a new fine-tuning method that incorporates an adapter module into a pre-trained base model and alternates weight updates by sections. We evaluated the proposed model through multiple experiments and demonstrated performance improvements compared to previous models. In the experimental results, Adapt-cMolGPT generated a greater number of novel and valid compounds compared to other models, with these generated compounds exhibiting properties similar to those of real molecular data. These results indicate that our proposed method is highly effective in designing drugs targeting specific proteins. Full article
(This article belongs to the Special Issue Computer-Aided Drug Design Strategies)
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14 pages, 1109 KiB  
Article
EDiffuRec: An Enhanced Diffusion Model for Sequential Recommendation
by Hanbyul Lee and Junghyun Kim
Mathematics 2024, 12(12), 1795; https://doi.org/10.3390/math12121795 - 8 Jun 2024
Cited by 1 | Viewed by 1825
Abstract
Sequential recommender models should capture evolving user preferences over time, but there is a risk of obtaining biased results such as false positives and false negatives due to noisy interactions. Generative models effectively learn the underlying distribution and uncertainty of the given data [...] Read more.
Sequential recommender models should capture evolving user preferences over time, but there is a risk of obtaining biased results such as false positives and false negatives due to noisy interactions. Generative models effectively learn the underlying distribution and uncertainty of the given data to generate new data, and they exhibit robustness against noise. In particular, utilizing the Diffusion model, which generates data through a multi-step process of adding and removing noise, enables stable and effective recommendations. The Diffusion model typically leverages a Gaussian distribution with a mean fixed at zero, but there is potential for performance improvement in generative models by employing distributions with higher degrees of freedom. Therefore, we propose a Diffusion model-based sequential recommender model that uses a new noise distribution. The proposed model improves performance through a Weibull distribution with two parameters determining shape and scale, a modified Transformer architecture based on Macaron Net, normalized loss, and a learning rate warmup strategy. Experimental results on four types of real-world e-commerce data show that the proposed model achieved performance gains ranging from a minimum of 2.53% to a maximum of 13.52% across HR@K and NDCG@K metrics compared to the existing Diffusion model-based sequential recommender model. Full article
(This article belongs to the Special Issue Advances in Recommender Systems and Intelligent Agents)
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