Search Results (726)

In outdoor environments, GNSS is commonly used for vehicle navigation and various location-based ITS services. However, in GNSS shadow roads such as tunnels and underground highways, it is challenging to provide these services. With the rapid expansion of GNSS shadow roads, the need for radio positioning technology that can serve the role of GNSS in these areas has become increasingly important to provide accurate vehicle navigation and various location-based ITS services. This paper proposes a new GNSS shadow road radio positioning technology using multidirectional BLE beacon signals. The structure of a multidirectional BLE beacon that radiates different BLE beacon signals in two or four directions is introduced, and explains the principle of differential RSSI technology to determine the vehicle’s location using these signals. Additionally, the technology used to determine the vehicle’s speed is described. A testbed was constructed to verify the performance of the developed multidirectional BLE beacon-based radio navigation system. The current status and future plans of the testbed installation are introduced, and the results of position and speed experiments using the testbed for constant speed and deceleration driving are presented. Full article

The integration of vision and language processing into a cohesive system has already shown promise with the application of large language models (LLMs) in medical image analysis. Their capabilities encompass the generation of medical reports, disease classification, visual question answering, and segmentation, providing yet another approach to interpreting multimodal data. This survey aims to compile all known applications of LLMs in the medical image analysis field, spotlighting their promises alongside critical challenges and future avenues. We introduce the concept of X-stage tuning which serves as a framework for LLMs fine-tuning across multiple stages: zero stage, one stage, and multi-stage, wherein each stage corresponds to task complexity and available data. The survey describes issues like sparsity of data, hallucination in outputs, privacy issues, and the requirement for dynamic knowledge updating. Alongside these, we cover prospective features including integration of LLMs with decision support systems, multimodal learning, and federated learning for privacy-preserving model training. The goal of this work is to provide structured guidance to the targeted audience, demystifying the prospects of LLMs in medical image analysis. Full article

Lipoma arborescens (LA) is a rare, non-neoplastic, intra-articular, mass-like lesion with villous lipomatous proliferation that replaces and distends the synovium, particularly in the knee joint. A few cases have been sporadically reported to affect the shoulder, elbow, wrist, hip, and ankle. The authors would like to present a rare and unique case of LA in the elbow joint with significant osteoarthritis in a 24-year-old young man, which suggests that a longstanding pre-existing LA can give rise to severe degenerative arthritis even in young patients unless diagnosed early and adequately treated. Full article

This study presents an analysis of the electromagnetic noise and vibration in a surface-mounted permanent magnet synchronous machine (SPMSM), focusing on their excitation sources. To investigate this, the excitation sources were identified through an analytical approach, and their effects on electromagnetic noise and vibration were evaluated using a finite element method (FEM)-based analysis approach. Additionally, an equivalent curved-beam model based on three-dimensional shell theory was applied to determine the deflection forces on the stator yoke, accounting for the tooth-modulation effect. The stator’s natural frequencies were derived through the characteristic equation in free vibration analysis. Modal analysis was performed to validate the analytically derived natural frequencies and to investigate stator deformation under the tooth-modulation effect across various vibration modes. Furthermore, noise, vibration, and harshness (NVH) analysis via FEM reveals that major harmonic components align closely with the natural frequencies, identifying them as primary sources of elevated vibrations. A comparative study between 8-pole–9-slot and 8-pole–12-slot SPMSMs highlights the impact of force variations on the stator teeth in relation to vibration and noise characteristics, with FEM verification. The proposed method provides a valuable tool for early-stage motor design, enabling the rapid identification of resonance operating points that may induce severe vibrations. This facilitates proactive mitigation strategies to enhance motor performance and reliability. Full article

This study presents a design and optimization methodology to enhance the power density and efficiency of wound field synchronous machines (WFSMs) by selectively applying grain-oriented electrical steel (GOES). Unlike conventional non-grain-oriented electrical steel (NOES), GOES exhibits significantly lower core loss along its rolling direction, making it suitable for regions with predominantly alternating magnetic fields. Based on magnetic field analysis, four machine configurations were investigated, differing in the placement of GOES within stator and rotor teeth. Finite element analysis (FEA) was employed to compare electromagnetic performance across the configurations. Subsequently, a multi-objective optimization was conducted using Latin Hypercube Sampling, meta-modeling, and a genetic algorithm to maximize power density and efficiency while minimizing torque ripple. The optimized WFSM achieved a 13.97% increase in power density and a 1.0% improvement in efficiency compared to the baseline NOES model. These results demonstrate the feasibility of applying GOES in rotating machines to reduce core loss and improve overall performance, offering a viable alternative to rare-earth permanent magnet machines in xEV applications. Full article

The goal of on-device continual learning is to enable models to adapt to streaming data without forgetting previously acquired knowledge, even with limited computational resources and memory constraints. Recent research has demonstrated that weighted regularization-based methods are constrained by indirect knowledge preservation and sensitive hyperparameter settings, and dynamic architecture methods are ill-suited for on-device environments due to increased resource consumption as the structure scales. In order to compensate for these limitations, replay-based continuous learning, which maintains a compact structure and stable performance, is gaining attention. The limitations of replay-based continuous learning are (1) the limited amount of historical training data that can be stored due to limited memory capacity, and (2) the computational resources of on-device systems are significantly lower than those of servers or cloud infrastructures. Consequently, designing strategies that balance the preservation of past knowledge with rapid and cost-effective updates of model parameters has become a critical consideration in on-device continual learning. This paper presents an empirical survey of replay-based continual learning studies, considering the nearest class mean classifier with replay-based sparse weight updates as a representative method for validating the feasibility of diverse edge devices. Our empirical comparison of standard benchmarks, including CIFAR-10, CIFAR-100, and TinyImageNet, deployed on devices such as Jetson Nano and Raspberry Pi, showed that the proposed representative method achieved reasonable accuracy under limited buffer sizes compared with existing replay-based techniques. A significant reduction in training time and resource consumption was observed, thereby supporting the feasibility of replay-based on-device continual learning in practice. Full article

Background/Objectives: The effects of combining chemotherapy with hormonal therapy based on hormone receptor (HR) expression in epithelial ovarian, fallopian tube, or primary peritoneal (EOC) remain unclear. This study evaluated the efficacy and safety of physician-chosen chemotherapy combined with hormonal therapy in patients with heavily pretreated advanced EOC, stratified by HR expression. Methods: This phase II, multicenter, pilot study included patients with heavily pretreated advanced EOC, allocated to estrogen receptor (ER)-dominant or progesterone receptor (PR)-dominant arms. Patients in the ER-dominant arm received tamoxifen plus physician-selected chemotherapy, while those in the PR-dominant arm received megestrol acetate (MA) plus chemotherapy. The primary outcome was the best objective response rate (ORR) for six months, assessed using an optimal two-stage Simon design. Results: Among 33 ER-dominant patients with high-grade serous carcinoma (HGSC), the six-month best ORR was 27.3% (3% complete response, 24.2% partial response). The six-month ORR and clinical benefit rate (CBR) were 18.8% and 37.5%, respectively, with 62.5% experiencing progressive disease (PD). Among three PR-dominant patients (two clear cell carcinoma and one HGSC), the six-month best ORR was 0%. The six-month ORR and CBR were also 0%, and all experienced PD within six months. No unacceptable toxicity related to tamoxifen or MA was encountered. Conclusions: In heavily pretreated advanced HGSC patients with ER-dominant expression, chemotherapy combined with tamoxifen showed encouraging clinical activity with favorable safety. While limited by the study design, these findings suggest a potential role for tailored hormonal therapy combined with chemotherapy based on HR expression in heavily pretreated advanced EOC. Clinical Trial Registration: KCT0004571 Full article

Background/Objectives: Lung cancer is a highly diverse disease, and reliable preclinical models that accurately reflect tumor characteristics are essential for studying lung cancer biology and testing new therapies. This study aimed to establish patient-derived tumor organoids (PDTOs) using small biopsy samples and surgical specimens to create a model system that preserves the genetic and histological features of the original tumors. Methods: PDTOs were generated from 163 lung cancer specimens, including 109 samples obtained using endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) or bronchoscopy, 52 surgical specimens, and 2 pleural fluid samples. The organoid establishment rate beyond passage three was assessed, and histological subtypes and genetic profiles were analyzed using immunohistochemical staining and targeted exome sequencing. Results: The overall PDTO establishment rate was 34.4% (56/163), and 44.6% (25/56) of these organoids retained the histological and genetic features of the parental tumors. Genetic analysis identified key mutations, including KRAS G12C, EGFR L858R, MET exon 14 skipping mutation, and ROS1 fusion. PDTOs successfully formed tumors in mice while maintaining the genetic characteristics of the original tumors. Co-culture of PDTOs with cancer-associated fibroblasts (CAFs) resulted in increased resistance to paclitaxel. In the co-culture model of PDTOs with immune cells, dose-dependent growth inhibition of PDTOs was observed in response to immune checkpoint inhibitors. Conclusions: PDTOs established from small biopsy and surgical specimens serve as a valuable model for studying lung cancer biology, tumor microenvironment interactions, and drug response. This model has the potential to improve personalized treatment strategies. Full article

Background/Objectives: Lactobacillus delbrueckii subsp. lactis CKDB001 (LL) has demonstrated anti-inflammatory, antioxidant, and lipid-regulatory effects in vitro and in vivo, including attenuation of hepatic steatosis and modulation of lipid metabolism. Given the known interactions between host metabolism and gut microbiota, these findings suggest a potential role for LL in modulating microbial composition under conditions of diet-induced obesity. This study aimed to investigate the microbiome-related effects of LL using an established murine model. To evaluate the effect of LL supplementation on gut microbial composition and predict microbial metabolic functions in mice with high-fat diet-induced obesity. Methods: Male C57BL/6J mice were fed a high-fat diet and administered LL orally for 12 weeks. Fecal samples were collected and analyzed using 16S rRNA gene sequencing. Microbial taxonomic profiles were assessed using linear discriminant analysis effect size, and functional predictions were performed using PICRUSt2. Results: LL supplementation significantly altered the gut microbiota by increasing the relative abundance of Lactobacillus and other commensal taxa while reducing the prevalence of pro-inflammatory genera such as Alistipes and Bilophila. Functional prediction analysis revealed a downregulation of lipopolysaccharide and ADP-L-glycero-β-D-manno-heptose biosynthesis pathways. Microbial functions associated with carbohydrate metabolism and short-chain fatty acid production were enriched in the LL-treated group. Conclusions: LL modulated gut microbial composition and suppressed pro-inflammatory microbial pathways while enhancing beneficial metabolic functions in high-fat diet-fed mice. These findings support the potential of LL as a safe and effective microbiota-targeted probiotic for managing obesity-related metabolic disorders. Full article

Vascular calcification significantly contributes to cardiovascular complications and limb loss in chronic kidney disease (CKD). To establish an optimal rat model for vascular calcification, we tested varying adenine concentrations and feeding durations in Sprague–Dawley rats (n = 72), divided into six groups (n = 12 each). The control group received a standard diet for 18 weeks. Group 1 was given 0.5% adenine for 4 weeks, followed by a standard diet. Group 2 received 0.5% adenine for 4 weeks, then 0.25% for 14 weeks. Group 3A received 0.5% adenine for 12 weeks and then standard diet; group 3B received 0.5% adenine for 12 weeks, followed by 0.25% for 6 weeks; group 3C received 0.5% adenine for 18 weeks. At week 18, vascular calcification was absent in the control and group 1. Groups 2 and 3A showed low incidence (12.5%), while groups 3B and 3C showed high incidence (66.7%). However, survival rates differed: 75.0% in 3B and 50.0% in 3C after 12 wk. Thus, 0.5% adenine for 12 weeks followed by 0.25% for 6 weeks effectively induced vascular calcification while maintaining acceptable survival, providing a practical model for studying CKD-related vascular pathology. Full article

Worker safety has been relatively overlooked in the rapidly growing aquaculture industry. To address this gap, industrial accident compensation insurance data—mainly from floating cage and seaweed farming—were analyzed to quantify accident types and frequencies, with a focus on human elements as root causes. Basic causes were selected based on IMO Resolution A/Res.884 and assessed through a worker awareness survey. Fault Tree Analysis (FTA), a Formal Safety Assessment technique, was applied to evaluate risks associated with these causes. The analysis identified organization at the farm site (23.3%), facility and equipment factors (22.8%), and people factors (21.4%) as the primary causes. Among secondary causes, personal negligence (13.2%), aging gear and poor maintenance (11.4%), and insufficient risk training (10.4%) were the most significant. Selective removal of these causes reduced the probability of human element-related accidents from 64.6% to 48.6%. While limited in scope to Korean data and self-reported surveys, the study demonstrates the value of combining quantitative data with worker perspectives. It provides foundational data for developing tailored safety strategies and institutional improvements—such as standardized procedures, multilingual education, and inclusive risk management—for sustainable safety in aquaculture. Full article

Background: This study investigated hematological and biochemical parameters, including cell population data (CPD), to evaluate their association with severity in COVID-19 and non-COVID-19 patients. Identifying these parameters could aid in disease monitoring and clinical decision-making. Methods: A retrospective analysis of 8401 patients, including 603 COVID-19 cases and 7546 non-COVID-19 cases, were conducted. Complete blood count (CBC) and routine chemistry results obtained near the time of real-time polymerase chain reaction testing were analyzed to assess their associations with disease severity. A matched cohort analysis was performed to adjust for potential confounding factors, such as age and sex. Results: COVID-19 patients with elevated neutrophil side fluorescence light (NE-SFL), platelet-to-lymphocyte ratio (PLR), glucose, and aspartate aminotransferase (AST), along with decreased plateletcrit, were more likely to experience severe outcomes, such as hospitalization or death. In addition, decreased hemoglobin, lymphocyte side scatter (LY-SSC), and albumin, as well as increased leukocyte and monocyte side scatter (MO-SSC), were associated with a greater severity, regardless of COVID-19 status. Conclusions: We identified hematologic and chemical assay biomarkers that correlate with severe COVID-19. These findings may provide important information regarding the disease progression and clinical management. Incorporating these biomarkers into clinical decision support systems could facilitate personalized treatment strategies, optimize resource allocation, and enable real-time severity stratification. Full article

After the transition of coronavirus disease 2019 (COVID-19) from a pandemic to an endemic phase, data on respiratory viral infections remain limited. This study compared the clinical outcomes of SARS-CoV-2, influenza virus (INFV), and respiratory syncytial virus (RSV) infections and investigated how underlying medical conditions influence disease severity. During Omicron subvariant dominant periods, we conducted a multicenter, retrospective cohort study including laboratory-confirmed cases of SARS-CoV-2, INFV, and RSV infections in hospitalized patients aged ≥ 19 years. We compared demographic characteristics and clinical outcomes and analyzed the association between underlying comorbidities and severity of infection. A total of 1850 cases with SARS-CoV-2, 98 with INFV, and 63 with RSV infections were analyzed. Notable differences in the occurrence of fever, cough, sputum, and dyspnea were observed among patients with the three different viral infections. Pneumonia was diagnosed more frequently in patients with RSV infection (65.6%) compared to those with INFV infection (42.9%) and SARS-CoV-2 (34.4%) (p < 0.01). For patients with SARS-CoV-2 infection, the risk of pneumonia increased by 47% in the moderate-risk group and 37% in the high-risk group. Among hospitalized patients, pneumonia was more frequently identified in patients with RSV infection, with statistical significance. Furthermore, the presence of medical conditions significantly increased the risk of developing pneumonia. Full article

Background: Hippocampal sclerosis (HS) is a hallmark of mesial temporal lobe epilepsy (MTLE). However, genetic studies on MTLE patients with HS (MTLE-HS) remain limited, especially in East Asian populations. This study aimed to identify genetic variants associated with MTLE-HS and elucidate their biological relevance through integrative genomic and transcriptomic analyses. Methods: We conducted a genome-wide association study (GWAS) on 157 Korean epilepsy patients, including 52 MTLE-HS subjects and 105 non-acquired focal epilepsy individuals without HS as controls. The splicing and expression quantitative trait locus (sQTL and eQTL, respectively) effects of significant variants were analyzed using GTEx datasets. Transcriptomic data from the hippocampi of MTLE-HS subjects and an epilepsy mouse model were examined to assess TMEM14A expression. Gene correlation enrichment analysis was performed to investigate potential associations with epilepsy-related phenotypes. Results: The GWAS identified rs6924849, located downstream of TMEM14A, as significantly associated with MTLE-HS. The sQTL analysis revealed that rs6924849 induces abnormal TMEM14A splicing in hippocampal tissue. Transcriptomic analyses showed reduced TMEM14A expression in MTLE-HS hippocampi, while mice with pilocarpine-induced epilepsy exhibited a transient increase in TMEM14A expression during the acute phase post-status epilepticus. Gene correlation enrichment analyses linked TMEM14A to seizure-related phenotypes in both humans and mice. Conclusions: This study identifies rs6924849 as a novel genetic variant associated with MTLE-HS in an East Asian population. The dysfunctional splicing and altered expression of TMEM14A may contribute to the neuronal loss characteristic of HS, as TMEM14A regulates apoptosis. These findings emphasize the potential role of TMEM14A in MTLE-HS pathogenesis from genomic and transcriptomic perspectives. Full article

Carbonaceous materials (CMs) have gained great attention as heterogeneous catalysts in water treatment because of their high efficiency and potential contribution to achieving carbon neutrality. Expanded graphite (EG) is ideal for studying CMs because the reactivity in CMs largely depends on graphitic structures, and most surface of EG is exposed, minimizing mass transfer resistance. However, EG is poor in adsorption and catalysis. In this study, EG was modified by simple thermal treatment to investigate the effects of characteristics of graphitic structures on reactivity. Tetracycline (TC) removal rate via activating peroxydisulfate (PDS) by the EG treated at 550 °C (EG550) was more than 10 times that of EG. The thermal modification did not significantly increase surfaces but led to increases in damaged, rough surfaces, graphitization degree, C content, defects, and C=O. Radical and non-radical pathways, such as SO₄^•−, O₂^•−, ¹O₂, and electron transfer, were involved in TC removal in EG550+PDS. TC degradation in EG550+PDS was initiated by hydroxylation, followed by demethylation, dehydroxylation, decarbonylation, and ring-opening. The ions ubiquitous in water systems did not significantly affect the performance of EG550+PDS, except for H₂PO₄⁻ and HCO₃⁻, suggesting the high potential of practical applications. This study demonstrated that graphitic structure itself and surface area are not detrimental in the catalytic reactivity of CMs, which is different from previous studies. Rather, the reactivity is governed by the characteristics, i.e., defects and functional groups of the graphitic structure. It is thought that this study provides valuable insights into the development of highly reactive CMs and the catalytic systems using them. Full article