Virtual Machines Performance Modeling with Support Vector Regressions

Virtualization is a key technology in cloudcomputing to render on-demand provisioning of virtual services.Xen, an open source paravirtualized virtual machine monitor(hypervisor), has been adopted by many leading data centersof the world today. A scheduler in Xen handles CPU resourcessharing among virtual machines hosted on the same physicalsystem. This study is focused on a scheduler in the currentXen release - the Credit scheduler. Credit uses two parameters(weight and cap) to fine tune CPU resources sharing. Previousstudies have shown that these two parameters can impact variousperformance measures of virtual machines hosted on Xen. In thisstudy, we present a holistic procedure to establish performancemodels of virtual machines. Empirical data of two commonly usedmeasures, namely calculation power and network throughput,were collected by simulations under various settings of weightand cap. We then employed a powerful machine learning tool(multi-kernel support vector regression) to learn performancemodels from the empirical data. These models were evaluatedsatisfactorily by using established procedures in machinelearning

Quasi-local mass in the covariant Newtonian space-time

In general relativity, quasi-local energy-momentum expressions have been constructed from various formulae. However, Newtonian theory of gravity gives a well known and an unique quasi-local mass expression (surface integration). Since geometrical formulation of Newtonian gravity has been established in the covariant Newtonian space-time, it provides a covariant approximation from relativistic to Newtonian theories. By using this approximation, we calculate Komar integral, Brown-York quasi-local energy and Dougan-Mason quasi-local mass in the covariant Newtonian space-time. It turns out that Komar integral naturally gives the Newtonian quasi-local mass expression, however, further conditions (spherical symmetry) need to be made for Brown-York and Dougan-Mason expressions.Comment: Submit to Class. Quantum Gra

Effectiveness of a Multifactorial Cardiovascular Risk Reduction Clinic for Diabetes Patients with Depression

Introduction Depression may attenuate the effects of diabetes interventions. Our ongoing Cardiovascular Risk Reduction Clinic simultaneously addresses hyperglycemia, hypertension, smoking, and hyperlipidemia. We examined the relationship between depression diagnosis and responsiveness to the Cardiovascular Risk Reduction Clinic. Methods We studied Cardiovascular Risk Reduction Clinic participants with diabetes who had a depression diagnosis and those with no mental health diagnosis. Our outcome measure was change in 20-year cardiovascular mortality risk according to the United Kingdom Prospective Diabetes Study (UKPDS) score. Results Of 231 participants, 36 (15.6%) had a depression diagnosis. Participants with a depression diagnosis had a higher baseline UKPDS score (56.8 [SD 21.3]) than participants with no mental health diagnosis (49.5 [SD 18.7], P =.04). After Cardiovascular Risk Reduction Clinic participation, mean UKPDS scores did not differ significantly (37.8 [SD 15.9] for no mental health diagnosis and 39.4 [SD 18.6] for depression diagnosis). Mean UKPDS score reduction was 11.6 [SD 15.6] for no mental health diagnosis compared with 18.4 [SD 15.9] for depression diagnosis (P =.03). Multivariable linear regression that controlled for baseline creatinine, number of Cardiovascular Risk Reduction Clinic visits, sex, and history of congestive heart failure showed significantly greater improvement in UKPDS score among participants with a depression diagnosis (ß = 6.0, P =.04) and those with more Cardiovascular Risk Reduction Clinic visits (ß = 2.1, P \u3c.001). Conclusion The Cardiovascular Risk Reduction Clinic program reduced cardiovascular disease risk among patients with diabetes and a diagnosis of depression. Further work should examine how depressive symptom burden and treatment modify the effect of this collaborative multifactorial program and should attempt to determine the durability of the effect

Advances, applications, and limitations of portable and rapid detection technologies for routinely encountered foodborne pathogens

Traditional foodborne pathogen detection methods are highly dependent on pre-treatment of samples and selective microbiological plating to reliably screen target microorganisms. Inherent limitations of conventional methods include longer turnaround time and high costs, use of bulky equipment, and the need for trained staff in centralized laboratory settings. Researchers have developed stable, reliable, sensitive, and selective, rapid foodborne pathogens detection assays to work around these limitations. Recent advances in rapid diagnostic technologies have shifted to on-site testing, which offers flexibility and ease-of-use, a significant improvement from traditional methods’ rigid and cumbersome steps. This comprehensive review aims to thoroughly discuss the recent advances, applications, and limitations of portable and rapid biosensors for routinely encountered foodborne pathogens. It discusses the major differences between biosensing systems based on the molecular interactions of target analytes and biorecognition agents. Though detection limits and costs still need further improvement, reviewed technologies have high potential to assist the food industry in the on-site detection of biological hazards such as foodborne pathogens and toxins to maintain safe and healthy foods. Finally, this review offers targeted recommendations for future development and commercialization of diagnostic technologies specifically for emerging and re-emerging foodborne pathogens

Costs and Effectiveness of Pharmacist-led Group Medical Visits for Type-2 Diabetes: A Multi-center Randomized Controlled Trial

Objectives The effectiveness and costs associated with addition of pharmacist-led group medical visits to standard care for patients with Type-2 Diabetes Mellitus (T2DM) is unknown. Methods Randomized-controlled-trial in three US Veteran Health Administration (VHA) Hospitals, where 250 patients with T2DM, HbA1c \u3e7% and either hypertension, active smoking or hyperlipidemia were randomized to either (1) addition of pharmacist-led group-medical-visits or (2) standard care alone for 13 months. Group (4–6 patients) visits consisted of 2-hour, education and comprehensive medication management sessions once weekly for 4 weeks, followed by quarterly visits. Change from baseline in cardiovascular risk estimated by the UKPDS-risk-score, health-related quality-of-life (SF36v) and institutional healthcare costs were compared between study arms. Results After 13 months, both groups had similar and significant improvements from baseline in UKPDS-risk-score (-0.02 ±0.09 and -0.04 ±0.09, group visit and standard care respectively, adjusted p Conclusions Addition of pharmacist-led group medical visits in T2DM achieved similar improvements from baseline in cardiovascular risk factors than usual care, but with reduction in the healthcare costs in the group visit arm 13 months after completion compared to the steady rise in cost for the usual care arm

Evaluation of the new AJCC staging system for resectable hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to assess the validity of the 7^thedition of the American Joint Committee on Cancer (AJCC) TNM system (TNM-7) for patients undergoing hepatectomy for hepatocellular carcinoma (HCC).</p> <p>Methods</p> <p>Partial hepatectomies performed for 879 patients from 1993 to 2005 were retrospectively reviewed. Clinicopathological factors, surgical outcome, overall survival (OS), and disease-free survival (DFS) were analyzed to evaluate the predictive value of the TNM-7 staging system.</p> <p>Results</p> <p>According to the TNM-7 system, differences in five-year survival between stages I, II, and III were statistically significant. Subgroup analysis of stage III patients revealed that the difference between stages II and IIIA was not significant (OS, <it>p </it>= 0.246; DFS, <it>p </it>= 0.105). Further stratification of stages IIIA, IIIB and IIIC also did not reveal significant differences. Cox proportional hazard models of stage III analyses identified additional clinicopathological factors affecting patient survival: lack of tumor encapsulation, aspartate aminotransferase (AST) values > 68 U/L, and blood loss > 500 mL affected DFS whereas lack of tumor encapsulation, AST values > 68 U/L, blood loss > 500 mL, and serum α-fetoprotein (AFP) values > 200 ng/mL were independent factors impairing OS. Stage III factors including tumor thrombus, satellite lesions, and tumor rupture did not appear to influence survival in the stage III subgroup.</p> <p>Conclusions</p> <p>In terms of 5-year survival rates, the TNM-7 system is capable of stratifying post-hepatectomy HCC patients into stages I, II, and III but is unable to stratify stage III patients into stages IIIA, IIIB and IIIC. Lack of tumor encapsulation, AST values > 68 U/L, blood loss > 500 mL, and AFP values > 200 ng/mL are independent prognostic factors affecting long-term survival.</p

Home‐Based Cardiac Rehabilitation Alone and Hybrid With Center‐Based Cardiac Rehabilitation in Heart Failure: A Systematic Review and Meta‐Analysis

Background Center‐based cardiac rehabilitation (CBCR) has been shown to improve outcomes in patients with heart failure (HF). Home‐based cardiac rehabilitation (HBCR) can be an alternative to increase access for patients who cannot participate in CBCR. Hybrid cardiac rehabilitation (CR) combines short‐term CBCR with HBCR, potentially allowing both flexibility and rigor. However, recent data comparing these initiatives have not been synthesized. Methods and Results We performed a meta‐analysis to compare functional capacity and health‐related quality of life (hr‐QOL) outcomes in HF for (1) HBCR and usual care, (2) hybrid CR and usual care, and (3) HBCR and CBCR. A systematic search in 5 standard databases for randomized controlled trials was performed through January 31, 2019. Summary estimates were pooled using fixed‐ or random‐effects (when I2\u3e50%) meta‐analyses. Standardized mean differences (95% CI) were used for distinct hr‐QOL tools. We identified 31 randomized controlled trials with a total of 1791 HF participants. Among 18 studies that compared HBCR and usual care, participants in HBCR had improvement of peak oxygen uptake (2.39 mL/kg per minute; 95% CI, 0.28–4.49) and hr‐QOL (16 studies; standardized mean difference: 0.38; 95% CI, 0.19–0.57). Nine RCTs that compared hybrid CR with usual care showed that hybrid CR had greater improvements in peak oxygen uptake (9.72 mL/kg per minute; 95% CI, 5.12–14.33) but not in hr‐QOL (2 studies; standardized mean difference: 0.67; 95% CI, −0.20 to 1.54). Five studies comparing HBCR with CBCR showed similar improvements in functional capacity (0.0 mL/kg per minute; 95% CI, −1.93 to 1.92) and hr‐QOL (4 studies; standardized mean difference: 0.11; 95% CI, −0.12 to 0.34). Conclusions HBCR and hybrid CR significantly improved functional capacity, but only HBCR improved hr‐QOL over usual care. However, both are potential alternatives for patients who are not suitable for CBCR

D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation

In the field of domain adaptation, a trade-off exists between the model performance and the number of target domain annotations. Active learning, maximizing model performance with few informative labeled data, comes in handy for such a scenario. In this work, we present D2ADA, a general active domain adaptation framework for semantic segmentation. To adapt the model to the target domain with minimum queried labels, we propose acquiring labels of the samples with high probability density in the target domain yet with low probability density in the source domain, complementary to the existing source domain labeled data. To further facilitate labeling efficiency, we design a dynamic scheduling policy to adjust the labeling budgets between domain exploration and model uncertainty over time. Extensive experiments show that our method outperforms existing active learning and domain adaptation baselines on two benchmarks, GTA5 -> Cityscapes and SYNTHIA -> Cityscapes. With less than 5% target domain annotations, our method reaches comparable results with that of full supervision.Comment: 14 pages, 5 figure