Design of a Web Based Underwater Acoustic Communication Testbed and Simulation Platform

Wireless Personal Communications - Underwater Wireless Sensor Networks (UWSNs) are playing a vital role in exploring the unseen underwater (UW) natural resources. However, performance evaluation of...     

A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

Synthesis,characterization and ion exchange properties of zirconium(IV) tungstoiodophosphate,a new cation exchanger

Zirconium(IV) tungstoiodophosphate has been synthesized under a variety of conditions. The most chemically and thermally stable sample is prepared by adding a mixture of aqueous solutions of 0·5 mol L⁻¹ sodium tungstate, potassium iodate and 1 mol L⁻¹ orthophosphoric acid to aqueous solution of 0·1 mol L⁻¹ zirconium(IV) oxychloride. Its ion exchange capacity for Na⁺ and K⁺ was found to be 2·20 and 2·35 meq g⁻¹ dry exchanger, respectively. The material has been characterized on the basis of chemical composition, pH titration, Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis. The effect on the exchange capacity of drying the exchanger at different temperatures has been studied. The analytical importance of the material has been established by quantitative separation of Pb²⁺ from other metal ions.     

Method to Characterize the Air Flow and Water Removal Characteristics During Vacuum Dewatering. Part II—Analysis and Characterization

This is part II of a study reported earlier on a method to characterize the air flow and water removal characteristics during vacuum dewatering. This article presents experimental data and analysis of results from the use of a cyclically actuated vacuum dewatering device for removing moisture from wetted porous materials such as paper with the intermittent application of vacuum and accompanying air flow though the material. Results presented include sheet moisture content as a function of residence time and hence water removal rate under a variety of process conditions. Also, experimental results on air flow through the wet porous structure and hence the role and importance of air flow during vacuum dewatering are presented. Vacuum dewatering process conditions include exit solids content between 11 and 20% solid under applied vacuum conditions of 13.5 to 67.7 kPa (4 to 20 in. Hg). Regression analysis indicated that the exit sheet moisture content exhibited a nonlinear relationship with residence time with exit solids reaching a plateau after a certain residence time. Final moisture content correlated linearly with the average overall flow rate of air through the paper sample and the basis weight of the material.     

A finite range failure model

In the present article the characterstics of a finite range failure time distribution, that includes the rectangular distribution as a particular case, are studied. When shape parameter surpass unity then the distribution is IFR otherwise it always remains IFRA. A graphic shape of the distribution is also formed for certain admissible values of the constants.     

Sarcoplasmic reticular Ca2+ pump ATPase activity in congestive heart failure due to myocardial infarction

OBJECTIVE: Earlier studies have shown a depression in the sarcoplasmic reticular (SR) Ca2+ uptake and gene expression in Ca2+ pump ATPase protein in congestive heart failure subsequent to myocardial infarction. It is the objective of this study to understand further the mechanisms of depressed SR Ca2+ pump activity in the failing heart. METHODS: Heart failure in rats was induced by occluding the left coronary artery for 16 weeks and the viable left ventricle was processed for the isolation of SR membranes. Sham-operated animals were used as control. The characteristics of SR Ca2+ pump ATPase in the presence of different concentrations of K+, Ca2+ and ATP were examined and the purity of these membranes was monitored by determining the marker enzyme activities. In addition to measuring changes in cyclic adenosine monophosphate (cAMP) protein kinase and Ca(2+)-calmodulin induced phosphorylation, alterations in SR phospholipid composition as well as sulfhydryl (SH) group content were investigated. RESULTS: Ca(2+)-stimulated ATPase activity, unlike Mg(2+)-ATPase activity, was depressed in the left ventricular SR from failing hearts as compared to control. The decrease in Ca(2+)-stimulated ATPase activity was seen at different concentrations of Ca2+, K+ and ATP but no changes in the affinities of the enzyme for Ca2+ and ATP were evident. The SR Ca(2+)-stimulated ATPase activities in the presence of both cAMP-dependent protein kinase and Ca(2+)-calmodulin were markedly decreased in the failing hearts when compared to control preparations. Furthermore, the 32P incorporation in the presence of cAMP-dependent protein kinase or Ca(2+)-calmodulin was also reduced in the experimental heart SR membranes. The phospholipid composition of the SR membranes from the failing heart was markedly altered. No changes in SH-group or the degree of cross contamination with other membranes were apparent in the failing heart SR. CONCLUSIONS: These results suggest that abnormalities in membrane phospholipid composition and phosphorylation of the enzyme may partly explain the observed depression in SR Ca2+ pump ATPase activity in heart failure following myocardial infarction.     

Potent and selective bicyclic lactam inhibitors of thrombin: Part 2: P1 modifications

The synthesis and antithrombotic activity of a series of nonpeptide bicyclic thrombin inhibitors is described. We have explored the SAR with modifications to the P1 site. The introduction of arginine mimetics at the P1 site led to potent and selective thrombin inhibitors.     

Autonomous mapping of HL7 RIM and relational database schema

Healthcare systems need to share information within and across the boundaries in order to provide better care to the patients. For this purpose, they take advantage of the full potential of current state of the art in healthcare standards providing interoperable solutions. HL7 V3 specification is an international message exchange and interoperability standard. HL7 V3 messages exchanged between healthcare applications are ultimately recorded into local healthcare databases, mostly in relational databases. In order to bring these relational databases in compliance with HL7, mappings between HL7 RIM (Reference Information Model) and relational database schema are required. Currently, RIM and database mapping is largely performed manually, therefore it is tedious, time consuming, error prone and expensive process. It is a challenging task to determine all correspondences between RIM and schema automatically because of extreme heterogeneity issues in healthcare databases. To reduce the amount of manual efforts as much as possible, autonomous mapping approaches are required. This paper proposes a technique that addresses the aforementioned mapping issue and aligns healthcare databases to HL7 V3 RIM specifications. Furthermore, the proposed technique has been implemented as a working application and tested on real world healthcare systems. The application loads the target healthcare schema and then identifies the most appropriate match for tables and the associated fields in the schema by using domain knowledge and the matching rules defined in the Mapping Knowledge Repository. These rules are designed to handle the complexity of semantics found in healthcare databases. The GUI allows users to view and edit/re-map the correspondences. Once all the mappings are defined, the application generates Mapping Specification, which contains all the mapping information i.e. database tables and fields with associated RIM classes and attributes. In order to enable the transactions, the application is facilitated with the autonomous code generation from the Mapping Specification. The Code Generator component focuses primarily on generating custom classes and hibernate mapping files against the runtime system to retrieve and parse the data from the data source—thus allows bi-directional HL7 to database communication, with minimum programming required. Our experimental results show 35–65% accuracy on real laboratory systems, thus demonstrating the promise of the approach. The proposed scheme is an effective step in bringing the clinical databases in compliance with RIM, providing ease and flexibility.     

Random-effects regression analysis of correlated grouped-time survival data

Random-effects regression modelling is proposed for analysis of correlated grouped-time survival data. Two analysis approaches are considered. The first treats survival time as an ordinal outcome, which is either right-censored or not. The second approach treats survival time as a set of dichotomous indicators of whether the event occurred for time periods up to the period of the event or censor. For either approach both proportional hazards and proportional odds versions of the random-effects model are developed, while partial proportional hazards and odds generalizations are described for the latter approach. For estimation, a full-information maximum marginal likelihood solution is implemented using numerical quadrature to integrate over the distribution of multiple random effects. The quadrature solution allows some flexibility in the choice of distributions for the random effects; both normal and rectangular distributions are considered in this article. An analysis of a dataset where students are clustered within schools is used to illustrate features of random-effects analysis of clustered grouped-time survival data.