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Background: Radial probe endobronchial ultrasound (radial EBUS) is widely used to diagnose pulmonary lesions; however, the diagnostic value of radial EBUS-guided transbronchial biopsy (TBB) varies, and its complications (especially the risk of bleeding) are not properly understood. Objectives: In this study, we evaluated the diagnostic performance and rate of complication of this procedure, and investigated the risk factors associated with the procedure-related bleeding events. Design: A retrospective cohort study. Methods: This was a retrospective study that included consecutive patients who underwent radial EBUS-guided TBB. Radial EBUS was performed under moderate sedation in inpatients or outpatients. The severity of bleeding was graded using the standardized definitions of bleeding. Results: Of 133 patients (median age, 69 years; men 57.1%) included, 41 were outpatients (30.8%). The diagnostic accuracy, sensitivity, and specificity for malignancy were 76.1% (89/117), 71.1% (69/97), and 100% (20/20), respectively. The diagnostic accuracy ranged from 66.9% to 79.0%, depending on the classification of undiagnosed cases as either false negatives or true negatives. Twenty-seven patients (20.3%) developed complications (pneumothorax, 3; pneumonia, 5; complicated pleural effusion, 2; bleeding event grade 2 or higher, 21). Of the 41 outpatients, two developed complications (pneumothorax without intervention, 1; grade 2 bleeding event, 1). Of the 21 patients (15.8%) with procedure-related bleeding events, 18 had grade 2, and three had grade 3 bleeding complications. In multivariate analysis, a large size of ⩾30 mm (adjusted odds ratio (OR), 5.09; p = 0.03) and central lesion (adjusted OR, 3.67; p = 0.03) were significantly associated with the risk of grade 2 or higher bleeding events. Conclusion: Our results suggest that radial EBUS-guided TBB is an accurate and safe method for diagnosing pulmonary lesions. Clinically significant procedure-related bleeding was rare. The central location and larger size (⩾30 mm) of pulmonary lesions were risk factors for grade 2 or higher bleeding events. [ABSTRACT FROM AUTHOR]

Background: The adverse effects of the COVID-19 pandemic on sleep have been well studied. However, whether the COVID-19 pandemic impacted positive airway pressure (PAP) adherence in patients with obstructive sleep apnea (OSA) remains unclear. Objectives: To evaluate the impact of the COVID-19 pandemic on adherence to PAP therapy in patients with OSA. Design: A retrospective cohort study, systematic review, and meta-analysis. Data sources and methods: The retrospective study included adults with OSA who received PAP prescriptions within the year before and the year after the start date of COVID-19 social distancing (22 March 2020) in South Korea. The threshold of clinical significance for PAP adherence was defined as 0.5 h/day. We also searched for relevant studies published up to 15 January 2023 using the MEDLINE and Embase databases. We performed a random-effects meta-analysis of our findings with the identified studies regarding the standardized mean change (SMC) with a 95% CI of PAP adherence. Results: Our study included a total of 306 patients (mean age, 59.7 years; men, 73.5%). The average daily PAP usage was 5.10 ± 1.63 h before the COVID-19 pandemic and 4.79 ± 1.96 h during the pandemic (mean difference, −0.31 h/day; 95% CI, −0.46 to −0.15 h/day; p < 0.001 using paired t -test). After identifying 10 observational before-and-after studies through a systematic review, we conducted a meta-analysis that included our original data and showed that adherence to PAP treatment was not different before and during the COVID-19 pandemic (SMC, 0.01; 95% CI, −0.18 to 0.19; p = 0.952). Conclusion: Although the COVID-19 pandemic had a statistically negative impact on adherence to PAP treatment in South Korea, the effect was not clinically relevant in patients with OSA. According to our meta-analysis, adherence to PAP treatment was not different before and during the COVID-19 pandemic in patients with OSA. Trial registration: PROSPERO database; No.: CRD42023414268; URL: https://www.crd.york.ac.uk/PROSPERO. [ABSTRACT FROM AUTHOR]

Climatic changes are now a global reality with widespread repercussions for individuals and businesses worldwide. The responsibility to adapt behaviors and protect the environment is shared by all of humanity. Business leaders can play a pivotal role in expediting this transformation by shifting their focus from pure profit-seeking to becoming value-driven entities that actively contribute to societal betterment while championing environmental conservation and sustainable profitability. This transition, however, poses certain challenges, notably the higher costs associated with ecofriendly materials, which can strain a company's financial equilibrium. Furthermore, a significant number of organizations overlook the untapped potential of their data, a valuable asset that could significantly bolster their competitive position. To address these challenges, this study aims to provide actionable guidance for business leaders by using a notable data framework to reassess their capabilities and dynamically adapt to external environments. Our method relies on data mining algorithms and business intelligence tools to report data. The results pinpoint which products are greatly in demand, so leaders can be assured their investment in redesigning products yields profit, improves product freshness, and eliminates waste. By bridging the gap between profitability and environmental responsibility, this study endeavors to empower businesses to thrive in a sustainable, value-driven future. [ABSTRACT FROM AUTHOR]

Despite the role of digital technologies in increasing the popularity of K-pop, little is known about how K-pop entertainment companies digitally transform their business models and the driving forces that shape this transformation. In this study, we present an in-depth case study of a pioneering K-pop entertainment company, SM Entertainment, whose founder's charismatic leadership and organizational capabilities contribute to the digital transformation of its business model through market-pioneering strategies and strategic learning derived from continuous interactions with changing business environments. This transition to the digital business model ultimately leads to sustainable competitive advantages in the marketplace. The important theoretical and practical implications of the findings are discussed. [ABSTRACT FROM AUTHOR]

Designing alternative fuels for advanced compression ignition engines necessitates a predictive model for cetane number (CN). In this study, the physics-informed graph neural networks are introduced for a reliable CN prediction by considering molecular features pertinent to the physical properties of molecules that affect CN. The reliability of measured data is another key factor to consider for improving the predictive model. Various experimental instruments for measuring CN exist, including standard and non-standard methods. In this regard, a systematic data quality analysis was carried out for the total 630 CNs collected from literature and new measurements in this study using Advanced Fuel Ignition Delay Analyzer (AFIDA). The results from this data curation process were reflected in the model by imposing lower sample weights on the data coming from less reliable measurement techniques. This approach effectively maximized the prediction accuracy while incorporating data from all available sources. Using the sample weights decreased the mean absolute error (MAE) up to 0.8 CN units. The accuracy was also improved by introducing the CN-related physical properties (the number of hydrogen bond donors and acceptors); the test set MAE is 5.74 and 7.01 for the model with and without such properties, respectively. Investigating molecular structural effects on CN was also carried out to gain chemical insights into factors used to design new fuel candidates. The dimensionality reduction analysis of feature vectors showed a clear clustering in terms of functional groups and CN and the structural effect derived from the model was consistent with the physicochemical insights. This physics-informed model and data curation would be helpful for accurate CN prediction and inform rational fuel design. [ABSTRACT FROM AUTHOR]

The high ϕ -sensitivity (η) of ignition delay time (τ IDT) is one of the desirable fuel properties for the high-load extension of advanced compression ignition engine. Recent studies revealed the effectiveness of a high dilution rate (x D) for enhancing η at the engine-relevant conditions. This study aims to quantify the effect of dilution on the η of isooctane using a combined experiment-simulation approach. The ignition delay of the isooctane/air mixture was measured with an Advanced Fuel Ignition Delay Analyzer (AFIDA) over the temperature range of 623 – 923 K at 10 bar pressure with global ϕ = 0.3 – 0.6, with and without 28.6% of additional N 2 dilution. For precise evaluation of experimental η , the facility effect of the AFIDA experiment was characterized with three-dimensional computational fluid dynamics (3-D CFD) simulation. The temperature in the combustion chamber from 3-D CFD indicated a substantial temporal dependency, varying up to ∼52 K by charge-cooling of fuel injection and heat transfer from the wall. We introduced the dimensionless number θ(t) for characterizing the temporal profile of chamber temperature. Consideration of the facility effect using θ(t) resulted in better agreement between the experimental η and zero-dimensional (0-D) kinetics simulation. The refined η were then further utilized to quantify the effectiveness of dilution to η. The extent of η enhancement with dilution strategy was maximized at the low-temperature chemistry regime, increasing η by 77% with a 28.6% dilution rate. Further analysis on the dilution effect was carried out using 0-D kinetics simulation, revealing the critical dimensionless numbers relevant to the effectiveness of dilution to η enhancement. This study is the first experiment-simulation combined research to quantify the effect of dilution on η , facilitating the kinetics model refinement for better reproduction of ϕ -sensitivity. [ABSTRACT FROM AUTHOR]