Contributions of higher order terms to nonlinear waves in fluid-filled elastic tubes: strongly dispersive case

In the present work, employing the nonlinear equations of an incompressible, isotropic and elastic thin tube and the approximate equations of an incompressible inviscid fluid, and then utilizing the modified reductive perturbation technique presented by us [15] the amplitude modulation of weakly nonlinear waves is examined. It is shown that the first order term in the perturbation expansion is governed by a nonlinear Schrödinger equation and the second order term is governed by the linearized Schrödinger equation with a nonhomogeneous term. In the longwave limit a travelling wave type of solution to these equations are also given.     

Endogenous and copper-induced lipid peroxidation and antioxidant activity of serum in hypercholesterolemic subjects

In order to observe the transport ability of peritoneum to small molecular substances, peritoneal equilibration test (PET) was performed in 52 CAPD patients. By analysing the relationship between peritoneal transport function and dialysis adequacy, we found the average urea KT/V and Cr were significantly lower in high and low transport groups (n = 6 and n = 2) than in high average and low average groups (n = 35 and n = 9). According to the results of PET, we adjusted the dialysis program of 11 patients and the dialysis adequacy was markedly improved. We concluded that PET was helpful for selecting and adjusting CAPD program, and discussed some questions which should be payed more attention in PET operation.     

Lipid peroxides, glutathione, gamma-glutamylcysteine synthetase and gamma-glutamyltranspeptidase activities in several tissues of rats following water-immersion stress

The effects of water-immersion restraint (WIR) stress on lipid peroxide, glutathione (GSH), glutathione peroxidase (GSH-Px), gamma-glutamylcysteine synthetase (gamma-GCS) and gamma-glutamyltranspeptidase (gamma-GT) activities in several tissues of rats were investigated. Hepatic and intestinal lipid peroxide levels were increased significantly in the WIR stress group. In both tissues, GSH levels were significantly decreased and gamma-GCS activity was significantly increased. In addition, gamma-GT activities remained unchanged in both tissues following WIR stress. However, lipid peroxide and GSH levels did not change in the stomach and brain in the WIR stress group compared to the control group. These results suggest that lipid peroxidation, but not the depression of GSH synthesis and/or the increase of GSH breakdown may be a factor in hepatic and intestinal GSH reduction following WIR stress.     

Regulation of conventional protein kinase C isozymes by phosphoinositide-dependent kinase 1 (PDK-1)

BACKGROUND: Phosphorylation critically regulates the catalytic function of most members of the protein kinase superfamily. One such member, protein kinase C (PKC), contains two phosphorylation switches: a site on the activation loop that is phosphorylated by another kinase, and two autophosphorylation sites in the carboxyl terminus. For conventional PKC isozymes, the mature enzyme, which is present in the detergent-soluble fraction of cells, is quantitatively phosphorylated at the carboxy-terminal sites but only partially phosphorylated on the activation loop. RESULTS: This study identifies the recently discovered phosphoinositide-dependent kinase 1, PDK-1, as a regulator of the activation loop of conventional PKC isozymes. First, studies in vivo revealed that PDK-1 controls the amount of mature (carboxy-terminally phosphorylated) conventional PKC. More specifically, co-expression of the conventional PKC isoform PKC betaII with a catalytically inactive form of PDK-1 in COS-7 cells resulted in both the accumulation of non-phosphorylated PKC and a corresponding decrease in PKC activity. Second, studies in vitro using purified proteins established that PDK-1 specifically phosphorylates the activation loop of PKC alpha and betaII. The phosphorylation of the mature PKC enzyme did not modulate its basal activity or its maximal cofactor-dependent activity. Rather, the phosphorylation of non-phosphorylated enzyme by PDK-1 triggered carboxy-terminal phosphorylation of PKC, thus providing the first step in the generation of catalytically competent (mature) enzyme. CONCLUSIONS: We have shown that PDK-1 controls the phosphorylation of conventional PKC isozymes in vivo. Studies performed in vitro establish that PDK-1 directly phosphorylates PKC on the activation loop, thereby allowing carboxy-terminal phosphorylation of PKC. These data suggest that phosphorylation of the activation loop by PDK-1 provides the first step in the processing of conventional PKC isozymes by phosphorylation.     

GRAIL: a scalable index for reachability queries in very large graphs

Given a large directed graph, rapidly answering reachability queries between source and target nodes is an important problem. Existing methods for reachability tradeoff indexing time and space versus query time performance. However, the biggest limitation of existing methods is that they do not scale to very large real-world graphs. We present a simple yet scalable reachability index, called GRAIL, that is based on the idea of randomized interval labeling and that can effectively handle very large graphs. Based on an extensive set of experiments, we show that while more sophisticated methods work better on small graphs, GRAIL is the only index that can scale to millions of nodes and edges. GRAIL has linear indexing time and space, and the query time ranges from constant time to being linear in the graph order and size. Our reference C++ implementations are open source and available for download at http://www.code.google.com/p/grail/.     

Monitoring web services’ quality of service: a literature review

Monitoring Quality of Service (QoS) compliance is an important procedure in web service environment. It determines whether users’ expectations are met, and becomes the vital factor for them to decide whether to continue paying for the service or not. The monitoring is performed by checking the actual services performance against the QoS stated in Service Level Agreement (SLA). In relation to that, the need for monitoring vague QoS specifications in SLA has become more apparent nowadays. This paper reviews the published literature on web services QoS monitoring. A total of 60 selected articles were systematically analyzed. There were 23 of the articles selected through restrictive search criteria while the other 37 were selected based on unrestrictive search criteria. The review shows that little evidence exists on monitoring vague QoS specifications of web services. Providing ability for monitoring QoS that is specified vaguely in SLA could give new insights and implications to web services field. This paper concludes with some recommended future works to construct the theory and perform the empirical research.     

Evaluating the Impact of User Characteristics and Different Layouts on an Interactive Visualization for Decision Making

There is increasing evidence that user characteristics can have a significant impact on visualization effectiveness, suggesting that visualizations could be designed to better fit each user's specific needs. Most studies to date, however, have looked at static visualizations. Studies considering interactive visualizations have only looked at a limited number of user characteristics, and consider either low‐level tasks (e.g., value retrieval), or high‐level tasks (in particular: discovery), but not both. This paper contributes to this line of work by looking at the impact of a large set of user characteristics on user performance with interactive visualizations, for both low and high‐level tasks. We focus on interactive visualizations that support decision making, exemplified by a visualization known as Value Charts. We include in the study two versions of ValueCharts that differ in terms of layout, to ascertain whether layout mediates the impact of individual differences and could be considered as a form of personalization. Our key findings are that (i) performance with low and high‐level tasks is affected by different user characteristics, and (ii) users with low visual working memory perform better with a horizontal layout. We discuss how these findings can inform the provision of personalized support to visualization processing.     

An in situ Raman study of the intercalation of supercapacitor-type electrolyte into microcrystalline graphite

An initial Raman study on the effects of intercalation for aprotic electrolyte-based electrochemical double-layer capacitors (EDLCs) is reported. In situ Raman microscopy is employed in the study of the electrochemical intercalation of tetraethylammonium (Et₄N⁺) and tetrafluoroborate (BF₄⁻) into and out of microcrystalline graphite. During cyclic voltammetry experiments, the insertion of Et₄N⁺ into graphite for the negative electrode occurs at an onset potential of +1.0 V versus Li/Li⁺. For the positive electrode, BF₄⁻ was shown to intercalate above +4.3 V versus Li/Li⁺. The characteristic G-band doublet peak (E_2g2(i) (1578 cm⁻¹) and E_2g2(b) (1600 cm⁻¹)) showed that various staged compounds were formed in both cases and the return of the single G-band (1578 cm⁻¹) demonstrates that intercalation was fully reversible. The disappearance of the D-band (1329 cm⁻¹) in intercalated graphite is also noted and when the intercalant is removed a more intense D-band reappears, indicating possible lattice damage. For cation intercalation, such irreversible changes of the graphite structure are confirmed by scanning electron microscopy (SEM).     

Type 2 Diabetes Risk Prediction Using Deep Convolutional Neural Network Based-Bayesian Optimization

Diabetes mellitus is a long-term condition characterized by hyperglycemia. It could lead to plenty of difficulties. According to rising morbidity in recent years, the world’s diabetic patients will exceed 642 million by 2040, implying that one out of every ten persons will be diabetic. There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’ lives. Due to its rapid development, deep learning (DL) was used to predict numerous diseases. However, DL methods still suffer from their limited prediction performance due to the hyperparameters selection and parameters optimization. Therefore, the selection of hyper-parameters is critical in improving classification performance. This study presents Convolutional Neural Network (CNN) that has achieved remarkable results in many medical domains where the Bayesian optimization algorithm (BOA) has been employed for hyperparameters selection and parameters optimization. Two issues have been investigated and solved during the experiment to enhance the results. The first is the dataset class imbalance, which is solved using Synthetic Minority Oversampling Technique (SMOTE) technique. The second issue is the model's poor performance, which has been solved using the Bayesian optimization algorithm. The findings indicate that the Bayesian based-CNN model superbases all the state-of-the-art models in the literature with an accuracy of 89.36%, F1-score of 0.88.6, and Matthews Correlation Coefficient (MCC) of 0.88.6.     

Feature sequencing in the rapid design system using a genetic algorithm

This paper addresses the feature sequencing problem in the Rapid Design System (RDS). The RDS is a feature-based design system that integrates product design and process planning. An important issue in feature-based process planning for machined parts is the order in which material is removed to form the resultant part. The order, or sequence, is partially dependent on the geometric relationships between features. The sequence affects the safety, the time it takes to machine the part, and the quality of the finished part. The sequence of material removal depends on two types of relations between features: (1) intersections and (2) interfeature associations. Both types of relations compound the search for an optimal sequence of material removal. Therefore, the research problem has been the discovery and development of a genetic algorithm (GA) that efficiently searches the solution space for all possible sequences and identifies the best sequences in terms of safety, time and quality.