Evaluation Boundary and Design Method for Insulating Packages

To evaluate the failure potential of insulated packaging to heat outside, a so-called evaluation boundary for insulating packages was proposed for designing and estimating insulating packages based on the heat transfer law between the environment and a packaged product through packaging. Three evaluation parameters were suggested for describing the failure mechanism of insulating packages. The validity of the presented evaluation boundary was verified by the experimental data. Finally, a new design method of insulating packages based on the boundary was proposed and an application example was performed as a demonstration. The results indicated that the three evaluation parameters (which are thermal load, adsorption ability of phase change material (PCM) and system thermal resistance of insulating packages) are the key parameters for designing insulating package and that the performance of insulating packages is only determined by the thermal load. Moreover, the proposed evaluation boundary shows a good agreement with experimental results, and the availability of the new method to design insulating packages was affirmative through the application example

New constraints on cosmic polarization rotation from the ACTPol cosmic microwave background B-Mode polarization observation and the BICEP2 constraint update

Recently ACTPol has measured the cosmic microwave background (CMB) B-mode and E-mode polarizations and obtained TE, EE, BB, TB and EB power spectra in the multipole range 225-8725. In our previous paper (Ap. J. 792 (2014) 35 [Paper I]), we have analyzed jointly the results of three experiments on the CMB B-mode polarization -- SPTpol, POLARBEAR and BICEP2 to include in the model, in addition to the gravitational lensing and the inflationary gravitational waves components, also the fluctuation effects induced by the cosmic polarization rotation (CPR), if it exists within the upper limits at the time. In this paper, we fit both the mean CPR angle and its fluctuation from the new ACTPol data, and update our fitting of CPR fluctuations using BICEP2 data taking the new Planck dust measurement results into consideration. We follow the method of Paper I. The mean CPR angle is constrained from the EB correlation power spectra to || < 14 mrad (0.8{\deg}) and the fluctuation (rms) is constrained from the BB correlation power spectra to 1/2 < 29.3 mrad (1.68{\deg}). Assuming that the polarization angle of Tau A does not change from 89.2 to 146 GHz, the ACTPol data give = 1.0 {\pm} 0.63{\deg}. These results suggest that the inclusion of the present ACTPol data is consistent with no CPR detection. With the new Planck dust measurement, we update our fits of the BICEP2 CPR fluctuation constraint to be 32.8 mrad (1.88{\deg}). The joint ACTpol-BICEP2-POLARBEAR CPR fluctuation constraint is 23.7 mrad (1.36{\deg}).Comment: 15 pages, 2 figures, 2 tables, version to match the accepted submission to ApJ. Unfortunately there is a sign error in equation (6b). This propagated to equations (7b) and (8a) and to the results for \alpha_\beta. The errors in the last raw of Table 1 had been overestimated and correcte

Serum high-sensitivity C-reactive protein levels in comorbid patients with type-2 diabetes mellitus and periodontal disease

Purpose: To investigate the relationship between serum levels of high-sensitivity C-reactive protein (hs-CRP) and the severity of periodontal disease in diabetics with periodontitis.Methods: Ninety patients were recruited for this study. They were divided into three groups, namely, group 1 (30 patients with type 2 diabetes mellitus (T2DM) and periodontal disease), group II (30 patients with T2DM only) and control (30 healthy individuals). Serum levels of hs-CRP and glycosylated hemoglobin (HbAc) were determined. Moreover, blood glucose (BG) and insulin (FNS) levels were determined in the fasted state, and their values used to compute insulin resistance index (Homa-IR).Results: Serum levels of FNS, FPG, HbAc and Homa-IR in group I patients were significantly higher (p &lt; 0.05) than those of control group. While the levels of BG and Homa-IR in the serum of patients in groups I and II were significantly higher (p &lt; 0.05) than those of control, marked reductions were seen in their values in group II, relative to group I. The serum levels of hs-CRP in group I and II were significantly increased (p &lt; 0.05) relative to control, but were lower in group II than in group I (p &lt; 0.05). Homa-IR was positively correlated with serum hs-CRP, FNS, BG, HbAc, and Homa-IR in groups I and II. Results from multiple regression analysis revealed significant effects of hs-CRP and HbAc on Homa-IR.Conclusion: Serum levels of hs-CRP in patients with T2DM and periodontitis are closely related to disease severity, insulin resistance and blood glucose level.Keywords: Type-2 diabetes mellitus, Periodontal disease, High-sensitivity C-reactive protein, Blood glucose, Insulin resistance, Correlatio

Predicting hyperlinks via hypernetwork loop structure

While links in simple networks describe pairwise interactions between nodes, it is necessary to incorporate hypernetworks for modeling complex systems with arbitrary-sized interactions. In this study, we focus on the hyperlink prediction problem in hypernetworks, for which the current state-of-art methods are latent-feature-based. A practical algorithm via topological features, which can provide understandings of the organizational principles of hypernetworks, is still lacking. For simple networks, local clustering or loop reflects the correlations among nodes; therefore, loop-based link prediction algorithms have achieved accurate performance. Extending the idea to hyperlink prediction faces several challenges. For instance, what is an effective way of defining loops for prediction is not clear yet; besides, directly comparing topological statistics of variable-sized hyperlinks could introduce biases in hyperlink cardinality. In this study, we address the issues and propose a loop-based hyperlink prediction approach. First, we discuss and define the loops in hypernetworks; then, we transfer the loop-features into a hyperlink prediction algorithm via a simple modified logistic regression. Numerical experiments on multiple real-world datasets demonstrate superior performance compared to the state-of-the-art methods