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"Sung, Kyung"
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Design Optimization of Lattice Structures under Compression: Study of Unit Cell Types and Cell Arrangements
Additive manufacturing enables innovative structural design for industrial applications, which allows the fabrication of lattice structures with enhanced mechanical properties, including a high strength-to-relative-density ratio. However, to commercialize lattice structures, it is necessary to define the designability of lattice geometries and characterize the associated mechanical responses, including the compressive strength. The objective of this study was to provide an optimized design process for lattice structures and develop a lattice structure characterization database that can be used to differentiate unit cell topologies and guide the unit cell selection for compression-dominated structures. Linear static finite element analysis (FEA), nonlinear FEA, and experimental tests were performed on 11 types of unit cell-based lattice structures with dimensions of 20 mm × 20 mm × 20 mm. Consequently, under the same relative density conditions, simple cubic, octahedron, truncated cube, and truncated octahedron-based lattice structures with a 3 × 3 × 3 array pattern showed the best axial compressive strength properties. Correlations among the unit cell types, lattice structure topologies, relative densities, unit cell array patterns, and mechanical properties were identified, indicating their influence in describing and predicting the behaviors of lattice structures.
Journal Article
Anticancer Activity of Bee Venom Components against Breast Cancer
While the survival rate has increased due to treatments for breast cancer, the quality of life has decreased because of the side effects of chemotherapy. Various toxins are being developed as alternative breast cancer treatments, and bee venom is drawing attention as one of them. We analyzed the effect of bee venom and its components on breast cancer cells and reviewed the mechanism underlying the anticancer effects of bee venom. Data up to March 2022 were searched from PubMed, EMBASE, OASIS, KISS, and Science Direct online databases, and studies that met the inclusion criteria were reviewed. Among 612 studies, 11 were selected for this research. Diverse drugs were administered, including crude bee venom, melittin, phospholipase A2, and their complexes. All drugs reduced the number of breast cancer cells in proportion to the dose and time. The mechanisms of anticancer effects included cytotoxicity, apoptosis, cell targeting, gene expression regulation, and cell lysis. Summarily, bee venom and its components exert anticancer effects on human breast cancer cells. Depending on the mechanisms of anticancer effects, side effects are expected to be reduced by using various vehicles. Bee venom and its components have the potential to prevent and treat breast cancer in the future.
Journal Article
Dietary fat intake and age modulate the composition of the gut microbiota and colonic inflammation in C57BL/6J mice
Background
More than half of the adult population worldwide is overweight or obese, while excess adiposity has been linked to chronic low-grade inflammation, contributing to the development of chronic diseases. Recent studies have showed that diet-induced alterations to the gut microbiota composition play a pivotal role in the development of obesity. However, the cause-effect relationship between obesity and gut microbiota composition is not yet fully understood. In this study, we investigated the short-term responses of gut microbiota composition to diets with different fat contents and their associations with inflammatory biomarkers.
Results
Sixty male C57BL/6 J mice were fed a normal diet (ND; 15% fat) or a high-fat diet (HFD; 45% fat) for 10 or 20 weeks. The relative proportion of the phylum Actinobacteria was elevated by the HFD and was positively associated with body weight and proinflammatory cytokines including TNF-α, IL-1β, and IL-6. The proportion of the phylum Firmicutes increased with aging and was also positively correlated with proinflammatory cytokines. The proportions of Actinobacteria and Firmicutes were inversely associated with tight junction proteins claudin-1 and E-cadherin, respectively. The proportions of the class Clostridia and the family Ruminococcaceae within the phylum Firmicutes were affected by both diet and age. In addition, the proportions of the phylum Bacteroidetes, the family Bacteroidaceae, and the genus
Bacteroides
decreased with aging and were inversely correlated with colonic proinflammatory cytokines representing a positive association with tight junction proteins.
Conclusions
Host age and dietary fat intake are important elements that induce proportional changes in gut microbiota, and these changes are also associated with systemic inflammation. This study provides evidence that diet affects the gut microbiota composition within a short period of time.
Journal Article
Improved Altitude Control Algorithm for Quadcopter Unmanned Aerial Vehicles
Quadcopter unmanned aerial vehicles continue to play important roles in several applications and the improvement of their control performance has been explored in a great number of studies. In this paper, we present an altitude control algorithm for quadcopters that consists of a combination of nonlinear and linear controllers. The smooth transition between the nonlinear and linear modes are guaranteed through controller gains that are obtained based on mathematical analysis. The proposed controller takes advantage and addresses some known shortcomings of the conventional proportional–integral–derivative control method. The algorithm is simple to implement, and we prove its stability through the Lyapunov theory. By prescribing certain flight conditions, we use numerical simulations to compare the control performance of our control method to that of a conventional proportional–derivative–integral approach. Furthermore, we use a DJI-F450 drone equipped with a laser ranging sensor as the experimental quadcopter platform to evaluate the performance of our new controller in real flight conditions. Numerical simulation and experimental results demonstrate the effectiveness of the proposed algorithm.
Journal Article
A Multimodal Fatigue Detection System Using sEMG and IMU Signals with a Hybrid CNN-LSTM-Attention Model
Physical fatigue significantly impacts safety and performance across industrial, athletic, and medical domains, yet its detection remains challenging due to individual variability and limited generalizability of existing methods. This study introduces a multimodal fatigue detection system integrating surface electromyography (sEMG) and inertial measurement unit (IMU) signals, processed through a hybrid convolutional neural network–long short-term memory–attention (CNN-LSTM-Attention) model. Fatigue was induced in 35 healthy participants via step-up-and-down exercises, with gait data collected during natural walking before and after fatigue. The model leverages sEMG from the gastrocnemius lateralis and IMU-derived jerk signals from the tibialis anterior and rectus femoris to classify fatigue states. Evaluated using leave-one-subject-out cross-validation (LOSOCV), the system achieved an accuracy of 87.94% with bilateral EMG signals and a balanced recall of 87.94% for fatigued states using a combined IMU-EMG approach. These results highlight the system’s robustness for personalized fatigue monitoring, surpassing traditional subject-dependent methods by addressing inter-individual differences.
Journal Article
Classification of Wintertime Atmospheric Teleconnection Patterns in the Northern Hemisphere
Energetics of the major atmospheric teleconnection patterns of the Northern Hemisphere winter are examined to investigate the role of baroclinic and barotropic energy conversions in their growth. Based on characteristics of the energetics and the horizontal structures, the patterns are classified into three general types: meridional dipole (D-type), wave (W-type), and hybrid (H-type). The primary energy conversion term that differentiates these patterns is the baroclinic energy conversion of the available potential energy from the climatology to the eddy field associated with the teleconnections. For this conversion term, D-type patterns exhibit the comparable conversion of potential energy via the eddy heat flux across the climatological thermal gradient in both the zonal and meridional directions. In contrast, baroclinic conversion for W-type patterns occurs primarily in the meridional direction, while H-type patterns exhibit a structure that combines the characteristics of the other two pattern types. An important secondary factor is barotropic conversion from the climatology to the eddy field, which takes place mainly in the regions where the climatological shear is strong. For the D-type patterns, conversion occurs on the flank of the climatological jet exit, while it occurs at the center of the jet exit for the W-type patterns. Last, for all the patterns, synoptic-time-scale eddies make a negative contribution via the baroclinic process, but a positive contribution via the barotropic process. Damping by diabatic heating weakens the temperature anomalies associated with the patterns.
Journal Article
Anticancer Activity of Snake Venom Against Breast Cancer: A Scoping Review
Breast cancer remains a leading cause of cancer-related mortality worldwide, necessitating innovative therapeutic approaches. This scoping review summarizes experimental evidence on the anticancer activity of snake venom and its bioactive components against breast cancer, drawing from a variety of in vitro and in vivo studies. Aimed at critically evaluating the therapeutic potential and underlying mechanisms, this review consolidates findings on venoms from multiple snake species, including both crude preparations and purified proteins or peptides, revealing a diversity of mechanisms of action. Reported effects include induction of apoptosis, generation of reactive oxygen species, disruption of cell membrane integrity, inhibition of cell proliferation and metastasis, and modulation of oncogenic signaling pathways. In vivo findings further indicate tumor growth inhibition and, in some cases, enhanced efficacy when venom-based agents are combined with nanoparticle delivery systems or conventional anticancer drugs. However, a significant proportion of evidence is limited to in vitro studies, with substantial heterogeneity in venom sources, extraction methods, dosages, and cancer models, which constrains generalizability. There is also a lack of systematic data on long-term toxicity, immunogenicity, off-target effects, pharmacokinetics, and formulation challenges. Taken together, these findings highlight snake venom-derived compounds as promising multi-targeted anticancer agents but underscore the urgent need for standardized formulations, rigorous preclinical safety assessments, and translational research to bridge the gap to clinical application. Future investigations should aim to isolate novel venom-derived compounds, refine delivery strategies, and undertake rigorous preclinical safety and pharmacokinetic studies—ultimately moving toward early-phase clinical evaluation to bridge the translational gap and assess the therapeutic potential of these agents.
Journal Article
Real-Time On-Device Continual Learning Based on a Combined Nearest Class Mean and Replay Method for Smartphone Gesture Recognition
Sensor-based gesture recognition on mobile devices is critical to human–computer interaction, enabling intuitive user input for various applications. However, current approaches often rely on server-based retraining whenever new gestures are introduced, incurring substantial energy consumption and latency due to frequent data transmission. To address these limitations, we present the first on-device continual learning framework for gesture recognition. Leveraging the Nearest Class Mean (NCM) classifier coupled with a replay-based update strategy, our method enables continuous adaptation to new gestures under limited computing and memory resources. By employing replay buffer management, we efficiently store and revisit previously learned instances, mitigating catastrophic forgetting and ensuring stable performance as new gestures are added. Experimental results on a Samsung Galaxy S10 device demonstrate that our method achieves over 99% accuracy while operating entirely on-device, offering a compelling synergy between computational efficiency, robust continual learning, and high recognition accuracy. This work demonstrates the potential of on-device continual learning frameworks that integrate NCM classifiers with replay-based techniques, thereby advancing the field of resource-constrained, adaptive gesture recognition.
Journal Article
Cognitive Behavioral Therapy for Migraine Headache: A Systematic Review and Meta-Analysis
Background and Objectives: Migraine headaches are chronic neurological diseases that reduce the quality of life by causing severe headaches and autonomic nervous system dysfunction, such as facial flushing, nasal stuffiness, and sweating. Their major treatment methods include medication and cognitive behavioral therapy (CBT). CBT has been used for pain treatment and various psychogenic neurological diseases by reducing pain, disability, and emotional disorders caused by symptoms of mental illness and improving the understanding of mental health. This study aimed to evaluate the effectiveness and safety of CBT in treating migraines. Materials and Methods: Seven electronic databases were searched from the date of inception to December 2020. Randomized controlled studies (RCTs) using CBT as an intervention for migraine were included. The primary outcome of this study was to determine the frequency of migraines and the intensity of migraines on Visual Analog Scale (VAS), the frequency of drug use, Migraine Disability Assessment (MIDAS), and Headache Impact Test (HIT-6) index. The two authors independently conducted the data extraction and quality assessment of the included RCTs, and conducted meta-analysis with RevMan V.5.4. Results: Among the 373 studies, 11 RCTs were included in this systematic review. Seven out of the 11 RCTs were conducted in the USA, and four were conducted in the UK, Germany, Iran, and Italy, respectively. Headache frequency and MIDAS scores were statistically significant reduced. In the subgroup analysis, headache strength was significantly reduced. Two of the included studies reported adverse effects, including worsening of migraine intensity and frequency, respiratory symptoms, and vivid memory of a traumatic event. Conclusions: CBT for migraine effectively reduced headache frequency and MIDAS score in meta-analysis and headache intensity subgroup analysis, with few adverse events. Additional RCTs with CBT for migraine headaches are needed for a more accurate analysis.
Journal Article