Chungwoon University

Background: Polysomnography (PSG) is the gold standard for diagnosing sleep disorders. However, the subjectivity of manual scoring can lead to inter-scorer variability, undermining diagnostic accuracy and subsequent clinical decisions. This study aims to quantitatively assess scoring concordance among multiple scorers across various clinical subgroups to identify the factors that contribute to interpretive discrepancies. Methods: We conducted a retrospective analysis of overnight diagnostic PSG data from adult patients at a tertiary university hospital sleep center. Interrater reliability was evaluated by three independent expert scorers for 30 subjects selected through stratified random sampling. The polysomnographic data were independently and blindly scored according to the American Academy of Sleep Medicine criteria, focusing on sleep stages, arousals, respiratory events, and leg movements, all scored in 30 s epochs. Interrater agreement was measured using Fleiss’ κ, along with 95% confidence intervals, and included subgroup analyses by diagnostic category. Results: The analysis included a total of 28,291 epochs from 30 adults across normal, insomnia, obstructive sleep apnea (OSA) [mild–severe], and periodic limb movement (PLM) disorder subgroups. The overall interrater agreement for sleep staging among the three scorers was nearly perfect (Fleiss’ κ = 0.932), with the highest concordance observed in stages W, N2, and R, and excellent agreement in stages N1 and N3. Respiratory events showed particularly high reliability, with near-perfect agreement for apnea (κ = 0.955) and substantial agreement for hypopnea, arousals, and PLMs. Pairwise analyses indicated the highest concordance between scorer 1 and scorer 3, while the agreement between scorer 1 and scorer 2 was lower, particularly for detecting arousals and limb movements. Subgroup analyses showed the highest and most stable agreement in moderate OSA, whereas severe OSA exhibited reduced reliability for sleep staging and arousal scoring, indicating increased scoring complexity with greater sleep fragmentation. Conclusions: Although expert PSG scoring demonstrates high overall reliability, significant variability persists in complex cases like severe OSA. These findings underscore the necessity for structured quality assurance and automated tools to improve diagnostic consistency in clinical practice.

This review paper systematically investigates the surface modification technology of wooden table tennis blades, with a particular focus on the inherent conflict between coating-induced protection and the preservation of acoustic performance—a critical yet underexplored aspect of blade design. While protective coatings are essential for enhancing durability against moisture, wear, and impact, they inevitably alter the blade’s vibrational characteristics and acoustic feedback, compromising the tactile–auditory perception that elite players rely upon. The current literature predominantly treats protection and acoustics as separate design objectives, lacking an integrated framework to resolve their inherent trade-off. To address this gap, this review establishes a material–structure–function integrated design paradigm that elucidates the synergistic optimization of coating protection and acoustic response. We systematically analyze the regulatory mechanisms of key coating parameters—specifically elastic modulus, density, and damping coefficient—on blade vibration modes and impact sound characteristics, demonstrating that conventional singular optimization inevitably leads to undesirable frequency shifts and diminished tactile feedback. Our synthesis of materials science, acoustic analysis, and biomechanics reveals that the key to synergy lies in constructing a mechanical impedance-matching transition system through material selection and thickness gradient design. Notably, we show that a multi-layer gradient coating architecture, guided by finite element simulation, can enhance protective performance by 40% while restricting acoustic deviation to within 5%, validating a rational “design–simulation–verification” closed-loop methodology. Furthermore, this review identifies critical research frontiers, including smart adaptive coatings and sustainable bio-based materials, and proposes a multi-objective optimization framework to bridge the gap between laboratory innovation and manufacturable, high-performance sporting equipment. This work provides a foundational theoretical roadmap for the next-generation design of competition-grade table tennis blades, balancing durability with the nuanced sensory demands of elite athletes.

In bulk heterojunction (BHJ) organic solar cells (OSCs) employing perylene diimide (PDI)-based non-fullerene acceptors, excessive intermolecular interactions among PDI units lead to severe aggregation and pronounced donor-acceptor phase separation, both of which critically limit device performance. To address these issues, numerous structurally engineered PDI derivatives have been developed. In particular, twisted multi-PDI architectures designed to suppress intermolecular aggregation have shown improved morphological control; however, such twisted structures are often highly amorphous, which reduces electron-transport efficiency and constrains OSC performance. In this work, we introduce a mixed-acceptor strategy combining a twisted PDI dimer (SF-PDI2) with a planar monomeric PDI (m-PDI) to balance aggregation and morphological uniformity. Ternary blend OSCs consisting of PTB7-Th as the donor and these two PDI acceptors exhibit systematic performance variations depending on their relative ratios. At the optimized composition (SF-PDI2:m-PDI = 90:10 by weight), the device outperforms single-acceptor systems, which is attributed to controlled aggregation arising from the complementary structural features of the two PDI acceptors. This study demonstrates that combining mixed PDI acceptors with similar molecular moieties enables precise control of aggregation, improving both morphology and photovoltaic performance.

Background/Objectives: This study evaluates the efficacy of hypoglossal nerve stimulation as an alternative intervention for pediatric patients with obstructive sleep apnea (OSA) unresponsive to standard therapies and examines the uniformity of therapeutic outcomes across different patient cohorts. Methods: An extensive systematic search was performed across four principal databases (PubMed, EMBASE, Cochrane Library, and Web of Science) utilizing keywords associated with pediatric OSA and hypoglossal nerve stimulation, encompassing studies up to July 2025 that provided objective polysomnographic metrics (e.g., apnea-hypopnea index [AHI] values) to enable the quantitative assessment of pre- and post-intervention effects in children. The primary outcome measured was the ratio of means (ROM), determined from pre-post data in single-group studies, with summary estimates obtained using the fixed-effects model. Results: The systematic review included nine eligible studies with a total of 140 pediatric subjects, the majority of whom were adolescents with Down syndrome. AHI meta-analysis outcomes indicated a marked improvement in OSA severity, yielding an overall ROM of 0.57 [95% confidence interval: 0.49-0.65]. The therapeutic benefit demonstrated a high degree of uniformity across cohorts, as indicated by minimal statistical heterogeneity (I2 = 16%, p = 0.30). Funnel plot assessment showed no statistically significant evidence of systematic publication bias. Conclusions: Current evidence suggests that hypoglossal nerve stimulation therapy is a safe, effective, and valuable alternative for pediatric OSA patients who do not respond to conventional therapies.

To increase the financial liquidity of startups, strengthen technology protection, and reinforce support for deep-tech sectors such as Artificial Intelligence(AI), South Korea is investing an annual public budget of 3.46 trillion KRW in 2026. This is executed through 508 support programs run by 111 institutions, including 15 central government ministries led by the Ministry of SMEs and Startups (MSS) and 96 local governments. The key performance indicators of companies receiving budget support include financial factors such as revenue and capital, investment factors such as the attraction of investments, investment amounts, and the number of investors, as well as other metrics like the number of media reports. To analyze the asymmetric effects of public enterprise support types, this study grouped companies into those that received support from the Ministry of SMEs and Startups (MSS) and the Ministry of Science and ICT (MSIT)—the primary ministries promoting enterprise support programs—and those that did not receive support. We collected and statistically analyzed the financial and investment-related corporate data of 77 usable companies out of 453. A Scoring Index was developed and applied to comprehensively compare the groups, which varied by the type of support program and whether or not they received support, using the collected corporate data. Through this, we empirically prove using data that public enterprise support programs act as a catalyst to resolve the resource constraints of startups and maximize entrepreneurship, such as innovativeness and risk-taking. Furthermore, going a step further from previous studies that analyzed simple performance differences based on whether government support was provided, this study investigates the asymmetric effects of public enterprise support on corporate performance. As it can be confirmed that there are differences in the timing of performance generation depending on the characteristics of the companies' Six Core Technologies(SCT) fields, this study is intended to be utilized as foundational data when establishing policy roadmaps for enterprise support specific to each corporate sector.