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Aerial Computing, utilizing unmanned aerial vehicles (UAVs), has emerged as a promising solution to enhance mobile cloud computing (MCC) infrastructure for the Internet of Things (IoT). The continuous generation of vast amounts of data by IoT devices requires efficient processing and monitoring for timely decision-making. However, wireless connections between IoT devices and remote servers can be unreliable, resulting in data loss. UAVs, with their increasing processing power and autonomy, can act as bridges between IoT devices and remote servers such as edge or cloud computing. In that context, this paper proposes a continuous time Markov chain (CTMC) models for an aerial computing system to evaluate system dependability metrics including availability and reliability. Sensitivity analysis is conducted to provide extended CTMC models with improved system availability. The proposed advanced model reduces downtime by 62 h compared to the baseline model, showcasing the potential of UAVs in enhancing the availability and reliability of MCC infrastructures. The use of UAVs and MCC in aerial computing is believed to be a win–win solution for cost-effective and energy-saving communication and computation services in various environments.

In the rapidly evolving field of autonomous unmanned aerial vehicles (UAVs), commonly referred to as drones, there is burgeoning interest from sectors such as logistics, online retail, and government agencies. The impetus for this interest is largely due to technological progress and innovation. This paper presents a model based on stochastic Petri nets (SPN) for evaluating the operational efficiency of drone delivery systems, with an emphasis on the completion times for tasks executed by either individual or multiple collaborating drones. Recognizing the limitation of drones’ operational duration, chiefly hindered by battery life, the paper suggests the creation of strategic charging stations and the adoption of cooperative delivery tactics as potential solutions, albeit with inherent costs. Two SPN models were developed within this study: one depicting solo drone missions and another depicting cooperative missions with package transfers between drones. These models facilitate the examination of several performance indicators, such as Utilization Level, Mean Mission Time, Delivery Rate, and the probability of delivering a set number of packages within a designated period. By utilizing Design of Experiments (DoE) methods for sensitivity analysis, the study pinpoints essential factors that impact the performance of deliveries and offers strategies for the enhancement of drone delivery networks. The paper concludes by asserting that strategic placement of charging stations coupled with collaborative delivery efforts can effectively mitigate the limitations posed by drones’ battery life, thereby augmenting the overall efficacy and feasibility of drone-based delivery services. The SPN models provide a robust predictive framework for drone delivery performance, aiding in improved planning and allocation of resources. The findings underscore the advantages of cooperative drone operations in urban logistics and call for additional research on the optimization of charging station placement and the refinement of collaborative drone strategies.

System dependability is pivotal for the reliable execution of designated computing functions. With the emergence of cloud-fog computing and microservices architectures, new challenges and opportunities arise in evaluating system dependability. Enhancing dependability in microservices often involves component replication, potentially increasing energy costs. Thus, discerning optimal redundancy strategies and understanding their energy implications is crucial for both cost efficiency and ecological sustainability. This paper presents a model-driven approach to evaluate the dependability and energy consumption of cloud-fog systems, utilizing Kubernetes, a container application orchestration platform. The developed model considers various determinants affecting system dependability, including hardware and software reliability, resource accessibility, and support personnel availability. Empirical studies validate the model’s effectiveness, demonstrating a 22.33% increase in system availability with only a 1.33% rise in energy consumption. Moreover, this methodology provides a structured framework for understanding cloud-fog system dependability, serves as a reference for comparing dependability across different systems, and aids in resource allocation optimization. This research significantly contributes to the efforts to enhance cloud-fog system dependability.

Urban Air Mobility (UAM) emerges as a transformative approach to address urban congestion and pollution, offering efficient and sustainable transportation for people and goods. Central to UAM is the Operational Digital Twin (ODT), which plays a crucial role in real-time management of air traffic, enhancing safety and efficiency. This study introduces a YOLOTransfer-DT framework specifically designed for Artificial Intelligence (AI) training in simulated environments, focusing on its utility for experiential learning in realistic scenarios. The framework’s objective is to augment AI training, particularly in developing an object detection system that employs visual tasks for proactive conflict identification and mission support, leveraging deep and transfer learning techniques. The proposed methodology combines real-time detection, transfer learning, and a novel mix-up process for environmental data extraction, tested rigorously in realistic simulations. Findings validate the use of existing deep learning models for real-time object recognition in similar conditions. This research underscores the value of the ODT framework in bridging the gap between virtual and actual environments, highlighting the safety and cost-effectiveness of virtual testing. This adaptable framework facilitates extensive experimentation and training, demonstrating its potential as a foundation for advanced detection techniques in UAM.

We perform a comparative study of the ex situ second-parameter pair globular clusters (GCs) M30 and M92, having similar metallicities but different horizontal branch morphologies. We obtain similar mean primordial carbon abundances for both clusters. However, M92 shows a large dispersion in carbon due to a more extended C–N anticorrelation, while M30 exhibits a higher primordial nitrogen abundance, suggesting that they have different chemical enrichment histories. Our new results confirm our previous result that M92 is a metal-complex GC showing a bimodal metallicity distribution. We also find that the metal-rich group of stars in M92 shows a helium enhancement as large as Δ Y ∼ 0.05 from the red giant branch bump V magnitudes, which can also be supported by (i) a lack of bright red giant branch stars, (ii) synthetic evolutionary horizontal branch population models and (iii) the more extended spatial distribution due to different degree of the diffusion process from their lower masses. We reinterpret the [Eu/Fe] measurements by others, finding that the two metallicity groups of stars in M92 have significantly different [Eu/Fe] abundances with small scatters. This strongly suggests that they formed independently out of well-mixed interstellar media in different environments. We suggest that M92 is a more complex system than a normal GC, most likely a merger remnant of two GCs or an even more complex system. In the Appendix, we address the problems with the recently developed color–temperature relations and the usage of broadband photometry in the populational taggings.

Multi-fidelity surrogate modeling (MFSM) methods are gaining recognition for their effectiveness in addressing simulation-based design challenges. Prior approaches have typically relied on recursive techniques, combining a limited number of high-fidelity (HF) samples with multiple low-fidelity (LF) datasets structured in hierarchical levels to generate a precise HF approximation model. However, challenges arise when dealing with non-level LF datasets, where the fidelity levels of LF models are indistinguishable across the design space. In such cases, conventional methods employing recursive frameworks may lead to inefficient LF dataset utilization and substantial computational costs. To address these challenges, this work proposes the extended hierarchical Kriging (EHK) method, designed to simultaneously incorporate multiple non-level LF datasets for improved HF model construction, regardless of minor differences in fidelity levels. This method leverages a unique Bayesian-based MFSM framework, simultaneously combining non-level LF models using scaling factors to construct a global trend model. During model processing, unknown scaling factors are implicitly estimated through hyperparameter optimization, resulting in minimal computational costs during model processing, regardless of the number of LF datasets integrated, while maintaining the necessary accuracy in the resulting HF model. The advantages of the proposed EHK method are validated against state-of-the-art MFSM methods through various analytical examples and an engineering case study involving the construction of an aerodynamic database for the KP-2 eVTOL aircraft under various flying conditions. The results demonstrated the superiority of the proposed method in terms of computational cost and accuracy when generating aerodynamic models from the given multi-fidelity datasets.

Abstract Background Adjuvant regional anesthesia is often selected for patients or procedures with high risk of pulmonary complications after general anesthesia. The benefit of adjuvant regional anesthesia to reduce postoperative pulmonary complications remains uncertain. In a prospective observational multicenter study, patients scheduled for non-cardiothoracic surgery with at least one postoperative pulmonary complication surprisingly received adjuvant regional anesthesia more frequently than those with no complications. We hypothesized that, after adjusting for surgical and patient complexity variables, the incidence of postoperative pulmonary complications would not be associated with adjuvant regional anesthesia. Methods We performed a secondary analysis of a prospective observational multicenter study including 1202 American Society of Anesthesiologists physical status 3 patients undergoing non-cardiothoracic surgery. Patients were classified as receiving either adjuvant regional anesthesia or general anesthesia alone. Predefined pulmonary complications within the first seven postoperative days were prospectively identified. Groups were compared using bivariable and multivariable hierarchical logistic regression analyses for the outcome of at least one postoperative pulmonary complication. Results Adjuvant regional anesthesia was performed in 266 (22.1%) patients and not performed in 936 (77.9%). The incidence of postoperative pulmonary complications was greater in patients receiving adjuvant regional anesthesia (42.1%) than in patients without it (30.9%) (site adjusted p = 0.007), but this association was not confirmed after adjusting for covariates (adjusted OR 1.37; 95% CI, 0.83–2.25; p = 0.165). Conclusion After adjusting for surgical and patient complexity, adjuvant regional anesthesia versus general anesthesia alone was not associated with a greater incidence of postoperative pulmonary complications in this multicenter cohort of non-cardiothoracic surgery patients.

It is well known that metal-poor red giant branch (RGB) stars show variations in some elemental abundances, including carbon, due to the internal mixing accompanied by their own in situ CN cycle in the hydrogen burning shell. With our new photometric carbon abundance measurements of RGB stars in M22 and other globular clusters (GCs) in our previous studies, M5, M3, and M92, we derive the carbon depletion rates against the V magnitude, d [C/Fe]/ M _V , for individual populations in each GC. We find the metallicity dependence of the carbon depletion rates, d [C/Fe]/ M _V ∝ −0.25[Fe/H]. Our results also suggest that the carbon depletion rates of the second generation (SG) of stars are larger than those of the first generation (FG) of stars in our sample GCs, most likely due to different internal temperature profiles with different initial helium abundances between the FG and SG. Our results can provide critical constraints both on understanding the mixing efficiency in the theoretical models, which is largely unknown, and on interpretation of the observational carbon abundance evolution of the bright halo RGB stars.

We present a multiple stellar population study of the metal-poor globular cluster (GC) M92 (NGC 6341), which is long known for the substantial metallicity dispersion, using our own photometric system. We find two groups with slightly different mean metallicities, the metal-poor (MP) stars with [Fe/H] _hk = −2.412 ± 0.03 and the metal-rich (MR) ones with −2.282 ± 0.002. The MP constitutes about 23% of the total mass with a more central concentration. Our populational tagging based on the [C/Fe] _ch and [N/Fe] _nh provides the mean n (P): n (I): n (E) = 32.2:31.6:36.2 (±2.4), where P, I, and E denote the primordial, intermediate, and extreme populations, respectively. Our populational number ratio is consistent with those of others. However, the MP has a significantly different populational number ratio than the mean value, and the domination of the primordial population in the MP is consistent with observations of Galactic GCs that less massive GCs contain larger fractions of the primordial population. Structural and constituent differences between the MP and MR may indicate that M92 is a merger remnant in a dwarf galaxy environment, consistent with recent suggestions that M92 is a GC in a dwarf galaxy or a remnant nucleus of the progenitor galaxy. Discrepancy between our method and those widely used for the Hubble Space Telescope photometry exists in the primordial population. Significant magnesium and oxygen depletions of −0.8 and −0.3 dex, respectively, and helium enhancement of Δ Y ≳ 0.03 are required to explain the presence of this abnormal primordial group. No clear explanation is available with limited information of detailed elemental abundances.

Abstract We investigated the larvicidal potential of 10 plant essential oils (EOs) against the Asian tiger mosquito Aedes albopictus. Among the EOs, larvicidal activity against Ae. albopictus was strongest in those derived from massoia (Massoia aromatica) and nutmeg (Myristica fragrans). Larvicidal activities of massoia and nutmeg EOs against Ae. albopictus were 95.0% and 85.0% at 50 μg/mL, respectively. A total of 4 and 14 compounds were identified from massoia and nutmeg, respectively, and two massoia lactones, C10 and C12, were isolated from massoia EO. Among the identified compounds, benzyl salicylate, terpinolene, C12 massoia lactone, sabinene, benzyl benzoate, methyl eugenol, and C10 massoia lactone exhibited the strong larvicidal activity. Cellulose nanocrystal (CNC)-stabilized Pickering emulsions of massoia and nutmeg EOs were developed to overcome the insolubility of EOs in water. CNC/massoia and CNC/nutmeg emulsions were stable for at least 10 days, and larvicidal activities of CNC/massoia PE and CNC/nutmeg were higher than those of crude massoia and nutmeg EOs. This study presents a CNC-stabilized PE, a suitable formulation for EOs, as a potential larvicide against Ae. albopictus.

Abstract Background Although promising, clinical translation of human mesenchymal stem or stromal cell-derived extracellular vesicles (MSC EV) for acute lung injury is potentially limited by significant production costs. The current study was performed to determine whether pretreatment of MSC EV with high molecular weight hyaluronic acid (HMW HA) would increase the therapeutic potency of MSC EV in severe bacterial pneumonia. Methods In vitro experiments were performed to determine the binding affinity of HMW HA to MSC EV and its uptake by human monocytes, and whether HMW HA primed MSC EV would increase bacterial phagocytosis by the monocytes. In addition, the role of CD44 receptor on MSC EV in the therapeutic effects of HMW HA primed MSC EV were investigated. In Pseudomonas aeruginosa (PA) pneumonia in mice, MSC EV primed with or without HMW HA were instilled intravenously 4 h after injury. After 24 h, the bronchoalveolar lavage fluid, blood, and lungs were analyzed for levels of bacteria, inflammation, MSC EV trafficking, and lung pathology. Results MSC EV bound preferentially to HMW HA at a molecular weight of 1.0 MDa compared with HA with a molecular weight of 40 KDa or 1.5 MDa. HMW HA primed MSC EV further increased MSC EV uptake and bacterial phagocytosis by monocytes compared to treatment with MSC EV alone. In PA pneumonia in mice, instillation of HMW HA primed MSC EV further reduced inflammation and decreased the bacterial load by enhancing the trafficking of MSC EV to the injured alveolus. CD44 siRNA pretreatment of MSC EV prior to incubation with HMW HA eliminated its trafficking to the alveolus and therapeutic effects. Conclusions HMW HA primed MSC EV significantly increased the potency of MSC EV in PA pneumonia in part by enhancing the trafficking of MSC EV to the sites of inflammation via the CD44 receptor on MSC EV which was associated with increased antimicrobial activity.

Due to the non-stop and rapid spreading of virus pandemics all over the world, traditional healthcare monitoring capabilities of hospitals and/or medical centers are under a severe over-load. Modern computing infrastructures with the harmony of various layers of computing paradigms (e.g., cloud/fog/edge computing) for healthcare monitoring are apparently the essential computing backbone that help access and process instantly the medical data of every single patient at the very edge of the healthcare system to combat with global or regional virus contagion. Previous studies proposed different computing system architectures for healthcare monitoring but few works considered the evaluation of pure performance of medical data transmission in a comprehensive manner. In this paper, we proposed an M/M/c/K queuing network model for the performance evaluation of an Internet of Healthcare Things (IoHT) infrastructure in association with a three layer cloud/fog/edge computing continuum. The model considers a life cycle of medical data from body-attached IoT sensors in edge layer all the way to local clients (e.g., local medical doctors, physicians) through fog layer and to remote clients (e.g., medical professionals, patient’s family members) through cloud layer. Furthermore, we also explore the impact of the alteration in system configuration and computing capability of computing layers in two scenarios on various performance metrics. Critical performance metrics related to quality of service are evaluated in a comprehensive manner, such as (i) mean response time of medical data transmission to fog (local) clients and to cloud (remote) clients, (ii) utilization of cloud/fog/edge computing layers, (iii) service throughput, (iv) number of medical messages in a period of time, and (v) drop rate. The simulation results pinpoint bottle-neck parameters and configurations of the IoHT infrastructure’s system architecture in relation to the frequency of medical data collection for health check of patients. Thus, the findings of this study can help improve medical administration in hospitals and healthcare centers and help design computing infrastructures in accordance for medical monitoring in the severe circumstances of virus pandemics.

Purpose The purpose of this study was to empirically analyze the relationship between a sports-for-all club members self-esteem and self-determination, conspicuous consumption, ethical consumption, product identification, positive word of mouth & repurchase intention through structural equation model analysis. Methods For this purpose, this study set 279 members at the nine sports-for-all club located in national capital region as the research subjects. In an effort to verify the proposed structural model, this study used SPSSWIN Ver. 23.0 and AMOS 18.0. Results First, self-esteem had a positive effect on conspicuous consumption. Second, self-determination had a positive effect on ethical consumption. Third, conspicuous consumption had a positive effect on product identification. Fourth, ethical consumption had a positive effect on product identification. Fifth, product identification had a positive effect on positive word of mouth. Sixth, product identification didn’t had a positive effect on repurchase intention. Seventh, positive word of mouth had a positive effect on repurchase intention.

OBJECTIVES Opioids are prescribed to treat moderate to severe pain. We investigated recent trends in opioid (morphine, oxycodone, fentanyl, and hydromorphone) prescriptions using data from the Korean National Health Insurance Service-National Sample Cohort between 2002 and 2015. METHODS The morphine milligram equivalent (MME) was calculated to standardize the relative potency of opioids. The number (cases) or amount (MME) of annual opioid prescriptions per 10,000 registrants was computed to analyze trends in opioid prescriptions after age standardization. Joinpoint regression analysis was conducted to calculate the annual percentage change and average annual percentage change (AAPC). RESULTS The number (cases) of prescriptions per 10,000 registrants increased from 0.07 in 2002 to 41.23 in 2015 (AAPC, 76.0%; 95% confidence interval [CI], 61.6 to 91.7). The MME per 10,000 registrants increased from 15.06 in 2002 to 40,727.80 in 2015 (AAPC, 103.0%; 95% CI, 78.2 to 131.3). The highest AAPC of prescriptions and MME per 10,000 registrants were observed in the elderly (60-69 years) and in patients treated at general hospitals. Fentanyl prescriptions increased most rapidly among the 4 opioids. CONCLUSIONS Consumption of opioids greatly increased in Korea over the 14-year study period.

It is necessary to develop a vehicle digital twin (DT) for urban air mobility (UAM) that uses an accurate, physics-based emulator to model the statics and dynamics of a vehicle. This is because the use of digital twins in the operation and control of UAM vehicles is essential for the UAM operational digital twin infrastructure (UAM-ODT). There are several issues that need to be addressed in this process: (i) the lack of digital twin engines for the digitalization (twinization) of the dynamics and control of UAM vehicles at the core of UAM-ODT systems; (ii) the lack of back-end system engineering in the development of UAM vehicle DTs; and (iii) the lack of fault-tolerant mechanisms for the DT cloud back-end system to run uninterrupted operations 24/7. On the other hand, software aging and rejuvenation are becoming increasingly important in a variety of computing scenarios as the demand for reliable and available services increases. With the increasing use of containerized systems, there is also a need for an orchestrator to support easy management and reduce operational costs. In this paper, an operational digital twin (ODT) of a typical urban air mobility (UAM) infrastructure is developed on a private cloud system based on Kubernetes using a proposed cloud-in-the-loop simulation approach. To ensure the ODT can provide uninterrupted operational control and services in UAM around the clock, we propose a methodology for investigating software aging in Kubernetes-based containerized clouds. We evaluate the behavior of Kubernetes software using the Nginx and K3S tools while they manage pods in an accelerated lifetime experiment. We continuously execute operations for creating and terminating pods, allowing us to observe the utilization of computing resources (e.g., CPU, memory, and I/O), the performance of the Nginx and K3S environments, and the response time of an application hosted in those environments. In some conditions and for specific metrics, such as virtual memory usage, we observed the effects of software aging, including a memory leak that is not fully cleared when the cluster is stopped. These issues could lead to system performance degradation and eventually compromise the reliability and availability of the system when it crashes due to memory space exhaustion or full utilization of swap space on the hard disk. This study helps with the deployment and maintenance of virtualized environments from the standpoint of system dependability in digital twin computing infrastructures where a large number of services are running under strict continuity requirements.

In this paper, we introduce a new formulation of the multivehicle point-to-point network problem to be utilised in urban air mobility (UAM) vertiport-to-vertiport network operations. Vehicle routing problems (VRPs) and their variants have previously been studied and applied in real-world situations, but these problems require additional depot locations, and not all the vehicles can travel to all the locations. In UAM operations, additional depot locations may not be required, and all vehicles can travel to all locations, meaning that existing routing problems are not suitable for application to the management of UAMs. Therefore, we propose a new formulation for UAM vertiport-to-vertiport operation by introducing new constraints. In addition, we integrate dynamic scheduling with the flight mission by controlling cruise speed and waiting in each UAM at each vertiport location to generate an arrival and departure schedule for different vertiports that can avoid collisions and increase the number of vehicles. A computational experiment is conducted using an MILP model, and the results show that although our formulation satisfies the problem definition, the computation time increases exponentially with an increase in the problem size. A case study is conducted in the Seoul area involving five vertiports, with 10- and 15-vehicle scenarios studied. This case study shows that the cruise speed variable is active only for the lower and upper bounds under dynamic scheduling, whereas the waiting time variable can be controlled between user-defined limits that can be applied to the management of vertiport-to-vertiport UAM operations.

In urban mobility, Vehicular Ad Hoc Networks (VANETs) provide a variety of intelligent applications. By enhancing automobile traffic management, these technologies enable advancements in safety and help decrease the frequency of accidents. The transportation system can now follow the development and growth of cities without sacrificing the quality and organisation of its services thanks to safety apps that include collision alerts, real-time traffic information, and safe driving applications, among others. Applications can occasionally demand a lot of computing power, making their processing impractical for cars with limited onboard processing capacity. Offloading of computation is encouraged by such a restriction. However, because vehicle mobility operations are dynamic, communication times (also known as link lifetimes) between nodes are frequently short. VANET applications and processes are impacted by such communication delays (e.g., the offloading decision when using the Computational Offloading technique). Making an accurate prediction of the link lifespan between vehicles is therefore challenging. The effectiveness of the communication time estimation is currently constrained by the link lifespan prediction methods used in the computational offloading process. This work investigates five machine learning (ML) algorithms to predict the link lifetime between nodes in VANETs in different scenarios. We propose the procedures required to carry out the link lifetime prediction method using existing ML techniques. The tactic creates datasets with the features the models need to learn and be trained. The SVR and XGBoost algorithms that were selected as part of the assessment process were trained. To make the prediction using the trained models, we modified the lifespan prediction function from an offloading approach. To determine the viability of applying link lifespan predictions from the models trained in the road and urban scenarios, we conducted a performance study. The findings indicate that compared to the conventional prediction strategy described in the literature, the suggested link lifetime prediction via regression approaches decreases prediction error rates. An offloading method from the literature is extended by the selected SVR. The task loss and recovery rates might be significantly reduced using the SVR. XGBoost outperformed its ML competitors in task recovery or drop rate by 70% to 80% in an assessed hypothesis compared to an offloading choice technique in the literature. With greater offloading rates from an application on the VANET, this effort is intended to give better efficiency in estimating this data using machine learning in various vehicular settings.

Statins have been recommended for use in atherosclerotic cardio-cerebrovascular disease (CCVD). The purpose of this study was to investigate the efficacy of five different types of statin in the secondary prevention of CCVD in patients. This study retrospectively designed and analyzed data from the National Health Insurance Service-National Health in Korea. Participants aged 40 to 69 years were categorized into five statin groups (atorvastatin, rosuvastatin, pitavastatin, simvastatin, and pravastatin). The primary composite outcome was defined as recurrence of CCVD or all causes of death. Cox proportional hazard regression models were adopted after stepwise adjustments for confounders to investigate the difference in efficacy among the different statins. Of the 755 final participants, 48 patients experienced primary composite outcomes. After adjustments, the hazard ratios (95% confidence intervals) for primary composite outcomes of atorvastatin, pitavastatin, and rosuvastatin groups were 0.956 (0.456-2.005), 1.347 (0.354-5.116), and 0.943 (0.317-2.803), respectively, when compared with the simvastatin group. There were no significant differences between the statins in efficacy for preventing recurrence of CCVD events and/or death in CCVD patients.

MethodsSepsis was induced by cotton smoke inhalation followed by intranasal administration of Pseudomonas aeruginosa in female (> 6 months) Balb/c and syndecan-1 knockout mice. Survival of mice, lung capillary endothelial glycocalyx integrity, lung water content, and vascular hyper-permeability were determined with or without HMW-SH treatment in these mice. Effects of HMW-SH on endothelial permeability and neutrophil migration were tested in in vitro setting.ResultsIn septic wildtype mice, we found a severely damaged pulmonary microvascular endothelial glycocalyx and elevated levels of shed syndecan-1 in the circulation. These changes were associated with significantly increased pulmonary vascular permeability. In septic syndecan-1 knockout mice, extravascular lung water content was higher, and early death was observed. The administration of HMW-SH significantly reduced mortality and lung water content in septic syndecan-1 knockout mice, but not in septic wildtype mice. In in vitro setting, HMW-SH inhibited neutrophil migration and reduced cultured endothelial cell permeability increases. However, these effects were reversed by the addition of recombinant syndecan-1 ectodomain.ConclusionsHMW-SH reduced lung tissue damage and mortality in the absence of syndecan-1 protein, possibly by reducing vascular hyper-permeability and neutrophil migration. Our results further suggest that increased shed syndecan-1 protein levels are linked with the inefficiency of HMW-SH in septic wildtype mice.

Human mesenchymal stem/stromal cells (hMSCs) are a promising therapy for acute respiratory distress syndrome (ARDS) and other inflammatory conditions. While considerable research has focused on paracrine effects and mitochondrial transfer that improve lung fluid balance, hMSCs are well known to have immunomodulatory properties as well. Some of these immunomodulatory properties have been related to previously reported paracrine effectors such as indoleamine-2,3-dioxygenase (IDO), but these effects cannot fully account for cell-contact dependent immunomodulation. Here, we report that CD40 is upregulated on hMSCs under the same conditions previously reported to induce IDO. Further, CD40 transcription is also upregulated on hMSCs by ARDS pulmonary edema fluid but not by hydrostatic pulmonary edema fluid. Transcription of CD40, as well as paracrine effectors TSG6 and PTGS2 remained significantly upregulated for at least 12 hours after withdrawal of cytokine stimulation. Finally, induction of this immune phenotype altered the transdifferentiation of hMSCs, one of their hallmark properties. CD40 may play an important role in the immunomodulatory effects of hMSCs in ARDS and inflammation.

The spread of the Coronavirus (COVID-19) pandemic across countries all over the world urges governments to revolutionize the traditional medical hospitals/centers to provide sustainable and trustworthy medical services to patients under the pressure of the huge overload on the computing systems of wireless sensor networks (WSNs) for medical monitoring as well as treatment services of medical professionals. Uncertain malfunctions in any part of the medical computing infrastructure, from its power system in a remote area to the local computing systems at a smart hospital, can cause critical failures in medical monitoring services, which could lead to a fatal loss of human life in the worst case. Therefore, early design in the medical computing infrastructure’s power and computing systems needs to carefully consider the dependability characteristics, including the reliability and availability of the WSNs in smart hospitals under an uncertain outage of any part of the energy resources or failures of computing servers, especially due to software aging. In that regard, we propose reliability and availability models adopting stochastic Petri net (SPN) to quantify the impact of energy resources and server rejuvenation on the dependability of medical sensor networks. Three different availability models (A, B, and C) are developed in accordance with various operational configurations of a smart hospital’s computing infrastructure to assimilate the impact of energy resource redundancy and server rejuvenation techniques for high availability. Moreover, a comprehensive sensitivity analysis is performed to investigate the components that impose the greatest impact on the system availability. The analysis results indicate different impacts of the considered configurations on the WSN’s operational availability in smart hospitals, particularly 99.40%, 99.53%, and 99.64% for the configurations A, B, and C, respectively. This result highlights the difference of 21 h of downtime per year when comparing the worst with the best case. This study can help leverage the early design of smart hospitals considering its wireless medical sensor networks’ dependability in quality of service to cope with overloading medical services in world-wide virus pandemics.

A critical drawback of battery-powered eVTOL UAVs is their limited range and endurance, and this drawback could be solved by using a combination of hydrogen fuel cells and batteries. The objective of this paper is to develop a sizing methodology for the lift+cruise-type eVTOL UAV powered by a hydrogen fuel cell and battery. This paper presents the constraints analysis method for forward flight/VTOL multi-mode UAV, the regression model for electric propulsion system sizing, a sizing method for an electric propulsion system and hydrogen fuel cell system, and a transition analysis method. The total mass of the UAV is iteratively calculated until convergence, and the optimization method is used to ensure that the sizing results satisfy the design requirements. The sizing results are the UAV’s geometry, mass, and power data. To verify the accuracy of the proposed sizing methodology, the sizing and the conceptual design phase results of a 25 kg hydrogen fuel-cell-powered UAV are compared. All parameters had an error within 10% and satisfied the design requirements.

BackgroundA diabetes risk score in Korean adults was developed and validated.MethodsThis study used the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) of 359,349 people without diabetes at baseline to derive an equation for predicting the risk of developing diabetes, using Cox proportional hazards regression models. External validation was conducted using data from the Korean Genome and Epidemiology Study. Calibration and discrimination analyses were performed separately for men and women in the development and validation datasets.ResultsDuring a median follow-up of 10.8 years, 37,678 cases (event rate=10.4 per 1,000 person-years) of diabetes were identified in the development cohort. The risk score included age, family history of diabetes, alcohol intake (only in men), smoking status, physical activity, use of antihypertensive therapy, use of statin therapy, body mass index, systolic blood pressure, total cholesterol, fasting glucose, and γ glutamyl transferase (only in women). The C-statistics for the models for risk at 10 years were 0.71 (95% confidence interval [CI], 0.70 to 0.73) for the men and 0.76 (95% CI, 0.75 to 0.78) for the women in the development dataset. In the validation dataset, the C-statistics were 0.63 (95% CI, 0.53 to 0.73) for men and 0.66 (95% CI, 0.55 to 0.76) for women.ConclusionThe Korean Diabetes Risk Score may identify people at high risk of developing diabetes and may be an effective tool for delaying or preventing the onset of condition as risk management strategies involving modifiable risk factors can be recommended to those identified as at high risk.

In this paper, we analyze diffusion strategies in which all nodes attempt to estimate a common vector parameter for achieving distributed estimation in adaptive networks. Under diffusion strategies, each node essentially needs to share processed data with predefined neighbors. Although the use of internode communication has contributed significantly to improving convergence performance based on diffusion, such communications consume a huge quantity of power in data transmission. In developing low-power consumption diffusion strategies, it is very important to reduce the communication cost without significant degradation of convergence performance. For that purpose, we propose a data-reserved periodic diffusion least-mean-squares (LMS) algorithm in which each node updates and transmits an estimate periodically while reserving its measurement data even during non-update time. By applying these reserved data in an adaptation step at update time, the proposed algorithm mitigates the decline in convergence speed incurred by most conventional periodic schemes. For a period p, the total cost of communication is reduced to a factor of 1/p relative to the conventional adapt-then-combine (ATC) diffusion LMS algorithm. The loss of combination steps in this process leads naturally to a slight increase in the steady-state error as the periodp increases, as is theoretically confirmed through mathematical analysis. We also prove an interesting property of the proposed algorithm, namely, that it suffers less degradation of the steady-state error than the conventional diffusion in a noisy communication environment. Experimental results show that the proposed algorithm outperforms related conventional algorithms and, in particular, outperforms ATC diffusion LMS over a network with noisy links.

This paper focuses on estimating dynamic stability derivatives using a computational fluid dynamics (CFD)-based force oscillation method, and on separating the coupled dynamic derivatives terms obtained from the method. A transient RANS solver is used to calculate the time history of aerodynamic moments for a test model oscillating about the center of gravity, from which the coupled dynamic derivatives are estimated. The separation of the coupled derivatives term is carried out by simulating simple harmonic oscillation motions such as plunging motion and flapping motion which can isolate the pitching moment due to AOA rate (Cmα˙) and the pitching moment due to pitch rate (Cmq), respectively. The periodic motions are implemented using a CFD dynamic mesh technique with user-defined function (UDF). For the validation test, steady and unsteady simulations are performed on the Army-Navy Finner Missile model. The static aerodynamic moments and pressure distribution, as well as the coupled dynamic derivative results from the pitching oscillation mode, show good agreement with the previously published wind tunnel tests and CFD analysis data. In order to separate the coupled derivative terms, two additional harmonic oscillation modes of plunging and flapping motions are tested with the angle of attack variations from 0 to 85 degrees at a supersonic speed to provide real insight on the missile maneuverability. The cross-validation study between the three oscillation modes indicates the summation of the individual plunging and flapping results becoming nearly identical to the coupled derivative results from the pitching motion, which implies the entire set of coupled and separated dynamic derivative terms can be effectively estimated with only two out of three modes. The advantages and disadvantages of each method are discussed to determine the efficient approach of estimating the dynamic stability derivatives using the forced oscillation method.

As populations become concentrated in cities, traffic congestion increases, and urban air mobility (UAM) is being considered to face this problem. Accordingly, many institutions and companies around the world are developing UAM vehicles, building infrastructure, and researching flight operating systems. In this study, three holding area concepts have been designed that can control air traffic flows and avoid bad weather conditions when UAM vehicles are operating. These holding areas have been considered to allow UAM vehicles to fly by avoiding collisions with other UAM vehicles or structures such as buildings. After validating the turning radius analysis with existing aircraft, a case study on the holding area concept design for the Seoul–GyungIn area was performed to determine whether UAM vehicles can turn within a narrow radius. It was not possible for winged-type UAM vehicles to turn across the Han River at cruise speed. The holding area concepts and the turning procedure of this study can be used as guidelines when designing UAM corridors or UAM flight routes.

Smart buildings in big cities are now equipped with an internet of things (IoT) infrastructure to constantly monitor different aspects of people’s daily lives via IoT devices and sensor networks. The malfunction and low quality of service (QoS) of such devices and networks can severely cause property damage and perhaps loss of life. Therefore, it is important to quantify different metrics related to the operational performance of the systems that make up such computational architecture even in advance of the building construction. Previous studies used analytical models considering different aspects to assess the performance of building monitoring systems. However, some critical points are still missing in the literature, such as (i) analyzing the capacity of computational resources adequate to the data demand, (ii) representing the number of cores per machine, and (iii) the clustering of sensors by location. This work proposes a queuing network based message exchange architecture to evaluate the performance of an intelligent building infrastructure associated with multiple processing layers: edge and fog. We consider an architecture of a building that has several floors and several rooms in each of them, where all rooms are equipped with sensors and an edge device. A comprehensive sensitivity analysis of the model was performed using the Design of Experiments (DoE) method to identify bottlenecks in the proposal. A series of case studies were conducted based on the DoE results. The DoE results allowed us to conclude, for example, that the number of cores can have more impact on the response time than the number of nodes. Simulations of scenarios defined through DoE allow observing the behavior of the following metrics: average response time, resource utilization rate, flow rate, discard rate, and the number of messages in the system. Three scenarios were explored: (i) scenario A (varying the number of cores), (ii) scenario B (varying the number of fog nodes), and (iii) scenario C (varying the nodes and cores simultaneously). Depending on the number of resources (nodes or cores), the system can become so overloaded that no new requests are supported. The queuing network based message exchange architecture and the analyses carried out can help system designers optimize their computational architectures before building construction.

In intelligent vehicles, extrinsic camera calibration is preferable to be conducted on a regular basis to deal with unpredictable mechanical changes or variations on weight load distribution. Specifically, high-precision extrinsic parameters between the camera coordinate and the world coordinate are essential to implement high-level functions in intelligent vehicles such as distance estimation and lane departure warning. However, conventional calibration methods, which solve a Perspective-n-Point problem, require laborious work to measure the positions of 3D points in the world coordinate. To reduce this inconvenience, this paper proposes an automatic camera calibration method based on 3D reconstruction. The main contribution of this paper is a novel reconstruction method to recover 3D points on planes perpendicular to the ground. The proposed method jointly optimizes reprojection errors of image features projected from multiple planar surfaces, and finally, it significantly reduces errors in camera extrinsic parameters. Experiments were conducted in synthetic simulation and real calibration environments to demonstrate the effectiveness of the proposed method.

We aimed to investigate if a home meal replacement (HMR), designed with a low ω-6/ω-3 fatty acid ratio, improves cardiometabolic parameters, including metabolic syndrome (MetS) in obese individuals. We conducted a monocentric, controlled, randomized crossover trial. The HMR contains higher protein and fat content, lower carbohydrate content, and a lower ω6FA/ω3FA ratio than the regular diet. Sixty-four participants were randomized into two groups and switched to the other group following a 4-week intervention. While subjects in the HMR group were provided three HMRs daily, those in the control group were requested to maintain their regular dietary pattern. We conducted paired t-tests, repeated measures analysis of variance, and McNemar tests before and after the intervention. Body mass index (BMI) and weight were lower in the HMR group after adjusting for age, sex, and total energy intake and significantly changed in the between-group differences. The waist circumference, systolic blood pressure, triglycerides, triglyceride–glucose index, and triglyceride to high-density lipoprotein cholesterol ratio were reduced in the HMR group (all p < 0.05). The percentage of subjects with MetS significantly decreased from 39.1% at baseline to 28.1% post-intervention (p = 0.035). Using the HMR for 4 weeks reduced the BMI, weight, and MetS prevalence in individuals with obesity. This trial was registered at clinicaltrials.gov (NCT04552574).

Path planning algorithms are of paramount importance in guidance and collision systems to provide trustworthiness and safety for operations of autonomous unmanned aerial vehicles (UAV). Previous works showed different approaches mostly focusing on shortest path discovery without a sufficient consideration on local planning and collision avoidance. In this paper, we propose a hybrid path planning algorithm that uses an anytime graph-based path planning algorithm for global planning and deep reinforcement learning for local planning which applied for a real-time mission planning system of an autonomous UAV. In particular, we aim to achieve a highly autonomous UAV mission planning system that is adaptive to real-world environments consisting of both static and moving obstacles for collision avoidance capabilities. To achieve adaptive behavior for real-world problems, a simulator is required that can imitate real environments for learning. For this reason, the simulator must be sufficiently flexible to allow the UAV to learn about the environment and to adapt to real-world conditions. In our scheme, the UAV first learns about the environment via a simulator, and only then is it applied to the real-world. The proposed system is divided into two main parts: optimal flight path generation and collision avoidance. A hybrid path planning approach is developed by combining a graph-based path planning algorithm with a learning-based algorithm for local planning to allow the UAV to avoid a collision in real time. The global path planning problem is solved in the first stage using a novel anytime incremental search algorithm called improved Anytime Dynamic A* (iADA*). A reinforcement learning method is used to carry out local planning between waypoints, to avoid any obstacles within the environment. The developed hybrid path planning system was investigated and validated in an AirSim environment. A number of different simulations and experiments were performed using AirSim platform in order to demonstrate the effectiveness of the proposed system for an autonomous UAV. This study helps expand the existing research area in designing efficient and safe path planning algorithms for UAVs.

Mobile Edge Computing (MEC) has emerged as a promising network computing paradigm associated with mobile devices at local areas to diminish network latency under the employment and utilization of cloud/edge computing resources. In that context, MEC solutions are required to dynamically allocate mobile requests as close as possible to their computing resources. Moreover, the computing power and resource capacity of MEC server machines can directly impact the performance and operational availability of mobile apps and services. The systems practitioners must understand the trade off between performance and availability in systems design stages. The analytical models are suited to such an objective. Therefore, this paper proposes Stochastic Petri Net (SPN) models to evaluate both performance and availability of MEC environments. Different to previous work, our proposal includes unique metrics such as discard probability and a sensitivity analysis that guides the evaluation decisions. The models are highly flexible by considering fourteen transitions at the base model and twenty-five transitions at the extended model. The performance model was validated with a real experiment, the result of which indicated equality between experiment and model with p-value equal to 0.684 by t-Test. Regarding availability, the results of the extended model, different from the base model, always remain above 99%, since it presents redundancy in the components that were impacting availability in the base model. A numerical analysis is performed in a comprehensive manner, and the output results of this study can serve as a practical guide in designing MEC computing system architectures by making it possible to evaluate the trade-off between Mean Response Time (MRT) and resource utilization.

(1) Background: Subclinical inflammation as a risk factor of cardiovascular diseases was clinically measured using C-reactive protein (CRP) level. (2) Methods: This study was cross-sectionally designed based the 2015–2018 Korean National Health and Nutrition Examination Survey (KNHANES). The ratio of daily omega-3 fatty acids to energy intake (ω3FA ratio) was classified into four quartile groups (Q1, p-value = 0.001), and 0.8% and 0.8% in women (p-value = 0.491), respectively. The prevalence of subclinical inflammation in males decreased with increasing quartile of ω3FA ratio (12.9%, 9.6%, 7.4%, and 7.7%, p-value = 0.033), while female prevalence was not significant among quartile groups. Compared to Q1, odds ratios (95% confidence intervals) for subclinical inflammation of Q2, Q3, and Q4 were 0.740 (0.465–1.177), 0.564 (0.341–0.930), and 0.549 (0.317–0.953) in males, and 1.066 (0.653–1.741), 1.105 (0.600–1.718), and 0.934 (0.556–1.571) in females after full adjustment. (4) Conclusion: The ω3FA ratio is associated with subclinical inflammation in men.

A pyrometallurgical reduction process for the recovery of copper and zinc from brass secondary slag (BSS) was studied. Specifically, the effect of reduction temperature and time on the conversion to metallic phases was investigated. The brass secondary slag was characterized by X-ray diffraction, inductively coupled plasma-atomic emission spectrometry, automatic elemental analysis, thermogravimetric analysis, and field emission scanning electron microscopy. A two-step reduction of BSS was identified. The step 1 comprised the reduction of ZnO, while the step 2 featured the reduction of ZnO·Al2O3. Furthermore, the application of a first-order reaction model with Arrhenius analysis, indicated a conversion of ZnO to Zn(g) that had a rate constant increasing from 1.4 ± 0.13 × 10−3 s−1 at 900 °C to 2.18 ± 0.15 × 10−2 s−1 at 1050 °C. This reaction had an activation energy of 233.2 ± 26.1 kJ/mol. Secondly, the conversion of ZnO·Al2O3 to Zn(g) and Al2O3 increased from 1.54 ± 0.21 × 10−5 s−1 at 900 °C to 1.09 ± 0.19 × 10−3 s−1 at 1050 °C, and the activation energy was 376.7 ± 22.4 kJ/mol. This reaction mechanism and its associated kinetic data can be applied to optimize the operation conditions of recycling processes for Cu-containing wastes.

BackgroundThe old age population, including the very old aged (≥ 85 years), is rapidly increasing, and femur neck fracture from accidents is commonly seen in the elderly. Use of bone cement during bipolar hemiarthroplasty can cause bone cement implantation syndrome.MethodsThis study was prospectively conducted on the elderly who were scheduled to undergo elective cemented bipolar hemiarthroplasty under spinal anesthesia. Patients were divided into 2 groups: the old age (65-84 years) and very old age groups (≥ 85 years). Hemodynamic parameters were recorded at the following time points: the start of the operation, femoral reaming, cement insertion, every 2 minutes after cement insertion for 10 minutes, femoral joint reduction, and the end of operation. When hypotension occurred, ephedrine was given.ResultsSixty-five patients in the old age group and 32 patients in the very old age group were enrolled. Mean ages were 78.9 and 89.4 years, respectively, in the old age and very old age groups. The very old age group showed constantly decreased levels of cardiac index and stroke volume from cementing until the end of the operation compared to the old age group. To maintain hemodynamic stability after cement insertion, the requirement of ephedrine was higher in the very old age group than in the old age group (13.52 ± 7.76 vs 8.65 ± 6.38 mg, P = 0.001).ConclusionsBone cement implantation during bipolar hemiarthroplasty may cause more prominent hemodynamic changes in very elderly patients. Careful hemodynamic monitoring and management are warranted in very elderly patients undergoing cemented bipolar hemiarthroplasty.

Increased atrial oxidative stress has an important role in inducing and maintaining atrial fibrillation (AF), and the activation of the small GTPase Rac1 contributes to the oxidative stress. We investigated the relationship of Rac1, atrial endothelial thromboprotective markers and AF inducibility and if simvastatin has a potential beneficial effect on a myocardial infarction (MI)-induced heart failure (HF) rat model. Rats were randomized into three groups (shams, MI group and simvastatin treatment group) and underwent echocardiography, AF induction studies and left atrial (LA) fibrosis analysis. Atrial Rac 1, sodium calcium exchanger (INCX), sarcoplasmic reticulum calcium ATPase (SERCA), endothelial nitric oxide synthase (eNOS) and induced nitric oxide synthase (iNOS) were measured. AF inducibility, AF duration and LA fibrosis were significantly higher in the MI group (p < 0.001 vs. sham), which were significantly reduced by simvastatin (p < 0.05 vs. MI). The reduced expressions of atrial eNOS, SERCA, thrombomodulin, tissue factor pathway inhibitor and tissue plasminogen activator in the MI group were significantly improved by simvastatin. Furthermore, the increased expression of atrial iNOS, INCX and Rac1 activity were significantly decreased by the simvastatin. Oxidative stress, endothelial dysfunction and thrombogenicity are associated with the promotion of AF in a rat model of ischemic HF. These were associated with increased Rac1 activity, and simvastatin treatment prevents these changes.

We presented fundamental stellar parameters and evolutionary statuses of six solar type detached eclipsing binaries whose masses are in the range of 0.97-1.43 M⊙. EK Cep and FL Lyr belong to the zero age main sequence. HS Hya, IT Cas and CD Tau are on the main sequence. Their ages are 1.3, 1.9 and 2.2 Gyr, respectively. Both component stars of AI Phe evolved to sub giants and its age is 4.0 Gyr. Those ages of the detached binary systems show good agreement with the time scale for synchronization and circularization of the binary systems.

BackgroundThis study compared the preventive effects of ramosetron and ondansetron on postoperative nausea and vomiting (PONV) in highly susceptible patients undergoing abdominal hysterectomy.MethodsIn a prospective, randomized, double-blinded study, a total of 120 highly susceptible women (nonsmokers, those receiving opioid-based IV patient-controlled analgesia [PCA]) undergoing abdominal hysterectomy were included in the study. Patients were divided into 2 groups and each group received either 0.3 mg of ramosetron or 4 mg of ondansetron, IV. All patients received fentanyl-based IV PCA during the 48 h postoperative periods. The incidences of PONV and side effects of 5-HT3 antagonists (headache and dizziness) were assessed at 3 intervals (

Since the early 1980s, the implantable intrathecal drug pump (ITDP) has been used increasingly to manage chronic pain. Prior to making a decision to implant an ITDP, trial administration of the intrathecal (IT) drug should be performed to estimate the effective dose for a starting set of implantable ITDPs. There is no standard method of trial IT drug administration, though. Therefore, this paper reports 20 cases of IT morphine trial with single and repetitive injections until the appropriate dose was attained with respect to analgesia and its side effects. The trial procedure was performed with daily sequential IT injections using morphine and 0.3% mepivacaine. Twelve out of the total of 20 patients had positive responses. Thus, it is inferred that daily sequential IT morphine injections combined with a placebo injection as a trial ITDP would be useful in evaluating the effectiveness and adverse effects of IT morphine infusion with clinically insignificant side effects.

A new method using thermal analysis database and optimization technique has been developed to substitute the original method what was based on trial and error. First, an original vacuum furnace was manufactured according to experiences. Modified baseline vacuum furnace which can be used in high temperature was produced from the original one by using experimental data and experiences. The results in 2 different conditions of nearly vacuum and argon ambient gas were investigated in order to define the worse but necessary condition between them. By comparing the analysis results with experimental results, the unknown thermal conductivity of insulator in high temperature has been found out. The calculated thermal conductivity of insulator has been applied to the process of thermal analysis database constructing under the condition of argon ambient gas which is the worse but necessary condition. In order to check the accuracy of constructed thermal analysis database, the interpolated results using constructed thermal analysis database have been compared with computational results. Finally, optimization study has been carried out to design an energy efficient, high temperature vacuum furnace which can fully satisfy user's design requirements by using the new method. Feasible optimal design has been obtained as a final product. With negligible computational cost, a high temperature vacuum furnace which has 31.9% reduction in the total heat was designed by using the new developed method.

We present HST NIC3 photometry of metal-rich globular clusters Palomar 6, Liller 1 and 47 Tuc (NGC 104). We discuss the interstellar reddening law for the HST NICMOS F110W/F160W photometric system which depends on the temperature of the source. The distance moduli and interstellar reddening values for Palomar 6 and Liller 1 are estimated by comparing the magnitudes and colors of RHB stars in the clusters with those of 47 Tuc. We obtain (m-M)0 = 14.48 mag and E(B-V) = 1.34 mag for Palomar 6 and (m-M)0 = 15.17 mag and E(B-V) = 2.50 mag for Liller 1.

CCD photometric observations of a W UMa type contact binary AH Cnc were performed for ten nights from December 1998 to May 1999 using a PM512 CCD camera and BVI filters attached to the 61cm reflector at Sobaeksan Optical Astronomy Observatory. New BVI light curves were analyzed with contact Mode 3 of the Wilson-Devinney binary model. We obtained photometric solutions and Roche geometry of this binary system. Through the analysis of the (O-C) diagram with all times of minimum light published so far and including hour's secular variations of orbital period and the mass transfer rate were calculated.

Statins, 3-hydroxy-3-methyl-glutaryl-CoA reductase inhibitors, are associated with the prevention of atrial fibrillation (AF) by pleiotropic effects. Recent clinical trial studies have demonstrated conflicting results on anti-arrhythmia between lipophilic and hydrophilic statins. However, the underlying mechanisms responsible for anti-arrhythmogenic effects of statins are largely unexplored. In this study, we evaluated the different roles of lipophilic and hydrophilic statins (simvastatin and pravastatin, respectively) in acetylcholine (100 µM)-activated K+ current (IKACh, recorded by nystatin-perforated whole cell patch clamp technique) which are important for AF initiation and maintenance in mouse atrial cardiomyocytes. Our results showed that simvastatin (1-10 µM) inhibited both peak and quasi-steady-state IKACh in a dose-dependent manner. In contrast, pravastatin (10 µM) had no effect on IKACh. Supplementation of substrates for the synthesis of cholesterol (mevalonate, geranylgeranyl pyrophosphate or farnesyl pyrophosphate) did not reverse the effect of simvastatin on IKACh, suggesting a cholesterol-independent effect on IKACh. Furthermore, supplementation of phosphatidylinositol 4,5-bisphosphate, extracellular perfusion of phospholipase C inhibitor or a protein kinase C (PKC) inhibitor had no effect on the inhibitory activity of simvastatin on IKACh. Simvastatin also inhibits adenosine activated IKACh, however, simvastatin does not inhibit IKACh after activated by intracellular loading of GTP gamma S. Importantly, shortening of the action potential duration by acetylcholine was restored by simvastatin but not by pravastatin. Together, these findings demonstrate that lipophilic statins but not hydrophilic statins attenuate IKACh in atrial cardiomyocytes via a mechanism that is independent of cholesterol synthesis or PKC pathway, but may be via the blockade of acetylcholine binding site. Our results may provide important background information for the use of statins in patients with AF.

We use BV CCD images to investigate the reality of the color gradient within a King type globular cluster NGC 7089. Surface photometry shows that there is a strong radial color gradient in the central region of the cluster in the sense of bluer center with the amplitude of -0.39 +/- 0.07 mag/arcsec2 in (B - V). In the outer region of the cluster, however, the radial color gradient shows a reverse case, i.e., redder toward the center. (B - V) color profile which was derived from resolved stars in VGC 7089 field also shows a significant color gradient in the central region of the clusters, indicating that lights from the combination of red giant stars and blue horizontal branch stars cause the radial color gradient. Color gradient of the outer region of NGC 7089 may be due to the unresolved background of the cluster. Similar color gradients in the central area of clusters have been previously observed exserved exclusively in highly concentrated systems classified as post core collapse clusters. We caution, however, to confirm the reality of the color gradient from resolved stars, we need more accurate imaging data of the cluster with exceptional seeing condition because the effect of completeness correlates with local density of stars.

The CCD photometric observations of W UMa-type eclipsing binary AB And were made from September 1994 to October 1996. New four primary minimum times were obtained form these observations. The analysis of times of minimum light for AB And confirms other previous studies that the orbital period of AB And have been changing as a form of sinusoidal variation. In this paper, we calculated the new orbital elements with linear and nonlinear quadratic term, and the best fit equation is derived with the assumption that the period variation of AB And changes sinusoidal pattern. From the sinusoidal term of this orbital element, we calculate period variation as 92 years with amplitude of 0d.059. However this result considering only sinusoidal term was not satisfied with our recent observations. Thus, by assuming another parabolic period variation with the sinusoidal pattern, we derived the best fit orbital elements. From the quadratic coefficient of this orbital elements, we calculated the secular variation of 0.73 seconds, and from the sinusoidal term, the period variation turned out to be 62.9 years with amplitude of 0d.024. If we assume only the sinusoidal period variation of AB And, the period has to be decreased with 10 years. However if we consider quadratic term with the sinusoidal period variation of the light elements, the period is expected to be increased. Therefore long-term observations of this binary system are required to confirm this issue.