An Online Resource Scheduling for Maximizing Quality-of-Experience in Meta Computing

Meta Computing is a new computing paradigm, which aims to solve the problem of computing islands in current edge computing paradigms and integrate all the resources on a network by incorporating cloud, edge, and particularly terminal-end devices. It throws light on solving the problem of lacking computing power. However, at this stage, due to technical limitations, it is impossible to integrate the resources of the whole network. Thus, we create a new meta computing architecture composed of multiple meta computers, each of which integrates the resources in a small-scale network. To make meta computing widely applied in society, the service quality and user experience of meta computing cannot be ignored. Consider a meta computing system providing services for users by scheduling meta computers, how to choose from multiple meta computers to achieve maximum Quality-of-Experience (QoE) with limited budgets especially when the true expected QoE of each meta computer is not known as a priori? The existing studies, however, usually ignore the costs and budgets and barely consider the ubiquitous law of diminishing marginal utility. In this paper, we formulate a resource scheduling problem from the perspective of the multi-armed bandit (MAB). To determine a scheduling strategy that can maximize the total QoE utility under a limited budget, we propose an upper confidence bound (UCB) based algorithm and model the utility of service by using a concave function of total QoE to characterize the marginal utility in the real world. We theoretically upper bound the regret of our proposed algorithm with sublinear growth to the budget. Finally, extensive experiments are conducted, and the results indicate the correctness and effectiveness of our algorithm

A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

AbstractMulti-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means (PFCM) kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means (FCM) clustering is sensitive to noises and possibility C-means (PCM) clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness

Pharmacokinetic model of unfractionated heparin during and after cardiopulmonary bypass in cardiac surgery

Background: Unfractionated heparin (UFH) is widely used as a reversible anti-coagulant in cardiopulmonary bypass (CPB). However, the pharmacokinetic characteristics of UFH in CPB surgeries remain unknown because of the lack of means to directly determine plasma UFH concentrations. The aim of this study was to establish a pharmacokinetic model to predict plasma UFH concentrations at the end of CPB for optimal neutralization with protamine sulfate. Methods: Forty-one patients undergoing CPB during cardiac surgery were enrolled in this observational clinical study of UFH pharmacokinetics. Patients received intravenous injections of UFH, and plasma anti-F-IIa activity was measured with commercial anti-F-IIa assay kits. A population pharmacokinetic model was established by using nonlinear mixed-effects modeling (NONMEM) software and validated by visual predictive check and Bootstrap analyses. Estimated parameters in the final model were used to simulate additional protamine administration after cardiac surgery in order to eliminate heparin rebound. Plans for postoperative protamine intravenous injections and infusions were quantitatively compared and evaluated during the simulation. Results: A two-compartment pharmacokinetic model with first-order elimination provided the best fit. Subsequent simulation of postoperative protamine administration suggested that a lower-dose protamine infusion over 24 h may provide better elimination and prevent heparin rebound than bolus injection and other infusion regimens that have higher infusion rates and shorter duration. Conclusion: A two-compartment model accurately reflects the pharmacokinetics of UFH in Chinese patients during CPB and can be used to explain postoperative heparin rebound after protamine neutralization. Simulations suggest a 24-h protamine infusion is more effective for heparin rebound prevention than a 6-h protamine infusion.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000350506400005&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Medicine, Research & ExperimentalSCI(E)[email protected]

Recent Advances in RecBole: Extensions with more Practical Considerations

RecBole has recently attracted increasing attention from the research community. As the increase of the number of users, we have received a number of suggestions and update requests. This motivates us to make some significant improvements on our library, so as to meet the user requirements and contribute to the research community. In order to show the recent update in RecBole, we write this technical report to introduce our latest improvements on RecBole. In general, we focus on the flexibility and efficiency of RecBole in the past few months. More specifically, we have four development targets: (1) more flexible data processing, (2) more efficient model training, (3) more reproducible configurations, and (4) more comprehensive user documentation. Readers can download the above updates at: https://github.com/RUCAIBox/RecBole.Comment: 5 pages, 3 figures, 3 table

Potential preventive markers in the intracerebral hemorrhage process are revealed by serum untargeted metabolomics in mice using hypertensive cerebral microbleeds

Hypertensive cerebral microbleeds (HCMB) may be the early stage of hypertensive intracerebral hemorrhage (HICH), which is a serious threat to health due to its high mortality and disability rates. The early clinical symptoms of HCMB may not be significant. Moreover, it is difficult to achieve early diagnosis and intervention for targeted prevention of HICH. Although hypertension (HTN) is a predisposition for HCMB, it remains unclear whether there is any difference between hypertensive patients with or without HCMB. Therefore, we carried out liquid chromatography-mass spectrometry (LC-MS) to analyze early biomarkers for HCMB in mice with hypertension and to lay the foundation for early prevention of HICH in hypertensive patients. In total, 18 C57 male mice were randomly divided into the HCMB (n = 6), HTN (n = 6), and control groups (CON, n = 6). Hematoxylin-eosin and diaminobenzidine staining were used to assess the reliability of the model. The metabolite expression level and sample category stability were tested using the displacement test of orthogonal partial least squares discriminant analysis (OPLS-DA). Significant differences in metabolites were screened out using variable importance in the projection (VIP > 1), which were determined using the OPLS-DA model and the P-value of the t-test (P < 0.05) combined with the nonparametric rank-sum test. With an area under the curve (AUC) > 0.85 and a P-value of 0.05, the receiver operating characteristic curve (ROC) was used to further screen the distinct metabolites of HCMB. Compared with the HTN and CON groups, the HCMB group had significantly higher blood pressure and lower average body weight (P < 0.05). Through untargeted LC-MS analysis, 93 distinct metabolites were identified in the HCMB (P < 0.05, VIP > 1) group. Among these potential biomarkers, six significantly decreased and eight significantly increased differential metabolites were found. Meanwhile, we found that the HCMB group had statistically distinct arginine and purine metabolism pathways (P < 0.05), and citrulline may be the most significant possible biomarker of HCMB (AUC > 0.85, P < 0.05). All of these potential biomarkers may serve as early biomarkers for HICH in hypertension

Development of a comprehensive method to analyse glazing systems with Parallel Slat Transparent Insulation material (PS-TIM)

In order to provide enhanced levels of indoor comfort and building energy conservation, significant improvements have been made in the design of glazed facades and window systems, yielding increases in thermal resistance while simultaneously maintaining access to daylight. Some of these approaches result in glazing systems with relatively complex structures and it is difficult to characterise their optical and thermal properties for use in building simulation. In this research, a comprehensive model has been developed to accurately predict the thermal and optical properties of complex glazing systems, and a workflow developed to yield detailed daylight and energy performance (heating, cooling and lighting) predictions of these systems when applied in buildings. Through this approach, the thermal characteristics of complex fenestration systems are obtained from a validated Computational Fluid Dynamics model, and a ray-tracing technique is used to obtain Bidirectional Scattering Distribution Function (BSDF) data to represent their optical characteristics. These characterises may be used in building simulation software (in this case EnergyPlus) to obtain building heating, cooling and lighting energy estimates for a room incorporating complex glazing systems. Detailed visual comfort predictions including useful daylight illuminance, daylight uniformity and glare may also be made, using a complementary optical model run using RADIANCE simulations. This workflow is implemented to investigate a room served by different Parallel Slat Transparent Insulation Materials (PS-TIM), which represents an example of a complex fenestration system. The workflow is used to explore the effect of slat pitch (i.e. the distance between neighbouring slats) on performance and was found to provide reasonable daylight and energy performance prediction. The results indicate that use of glazing systems with PS-TIM can provide homogenous daylight distribution and up to 33.6% energy reduction when the simulation is run using weather data for London