Effect of elemental sulfur in the crosslinking reaction of poly(vinyl chloride) with tetramethyl thiuram disulfide

The effect of elemental sulfur (S₈) and tetramethyl thiuram disulfide (TMTD) on the chemical crosslinking of PVC is studied. The tensile strength, elongation at break, and gel content of crosslinked and uncrosslinked PVC molded samples, cured at different times in hot air, are evaluated. It was found that crosslinking PVC with TMTD improves its mechanical properties, and adding S₈ produces a slight improvement. Also, the S₈ presence accelerated the PVC/TMTD crosslinking reaction when the crosslinking reaction was carried out under shear forces, but not when the curing was done in hot air, where the S₈ retards the process.     

Evaluation of messaging middleware for high-performance cloud computing

Cloud computing is posing several challenges, such as security, fault tolerance, access interface singularity, and network constraints, both in terms of latency and bandwidth. In this scenario, the performance of communications depends both on the network fabric and its efficient support in virtualized environments, which ultimately determines the overall system performance. To solve the current network constraints in cloud services, their providers are deploying high-speed networks, such as 10 Gigabit Ethernet. This paper presents an evaluation of high-performance computing message-passing middleware on a cloud computing infrastructure, Amazon EC2 cluster compute instances, equipped with 10 Gigabit Ethernet. The analysis of the experimental results, confronted with a similar testbed, has shown the significant impact that virtualized environments still have on communication performance, which demands more efficient communication middleware support to get over the current cloud network limitations.     

Using k-nn and discriminant analyses to classify rain forest types in a Landsat TM image over northern Costa Rica

Conservation and land use planning in humid tropical lowland forests urgently need accurate remote sensing techniques to distinguish among floristically different forest types. We investigated the degree to which floristically and structurally defined Costa Rican lowland rain forest types can be accurately discriminated by a non-parametric k nearest neighbors (k-nn) classifier or linear discriminant analysis. Pixel values of Landsat Thematic Mapper (TM) image and Shuttle Radar Topography Mission (SRTM) elevation model extracted from segments or from 5 × 5 pixel windows were employed in the classifications. 104 field plots were classified into three floristic and one structural type of forest (regrowth forest). Three floristically defined forest types were formed through clustering the old-growth forest plots (n = 52) by their species specific importance values. An error assessment of the image classification was conducted via cross-validation and error matrices, and overall percent accuracy and Kappa scores were used as measures of accuracy. Image classification of the four forest types did not adequately distinguish two old-growth forest classes, so they were merged into a single forest class. The resulting three forest classes were most accurately classified by the k-nn classifier using segmented image data (overall accuracy 91%). The second best method, with respect to accuracy, was the k-nn with 5 × 5 pixel windows data (89% accuracy), followed by the canonical discriminant analysis using the 5 × 5 pixel window data (86%) and the segment data (82%). We conclude the k-nn classifier can accurately distinguish floristically and structurally different rain forest types. The classification accuracies were higher for the k-nn classifier than for the canonical discriminant analysis, but the differences in Kappa scores were not statistically significant. The segmentation did not increase classification accuracy in this study.     

AC electrokinetic pumping on symmetric electrode arrays

AC electro-osmotic (ACEO) pumping is experimentally demonstrated on a symmetric gold electrode array. Using asymmetric connection of electrodes to the applied AC voltage, spatial asymmetry along the array is created, which produces unidirectional flow of electrolyte. An aqueous solution of 100 μM KCl is selected as the pumping fluid. The liquid velocity obtained as a function of voltage and frequency is compared to that generated using travelling-wave electroosmosis (TWEO) with the same electrode array. The expected velocities from the linear electrokinetic models of ACEO and TWEO are computed numerically. The comparison shows that TWEO generates greater velocity amplitudes and the streamlines are smoother than those generated by ACEO.     

Prediction of the percentages of cows'', goats'' and ewes'' milk in “Iberico” cheese by electrophoretic analysis of whey proteins

Stepwise multiple linear regression (SMLR) and principal components regression (PCR) have been used to predict the percentages of cows', goats' and ewes' milk in Iberico cheese, using the results obtained by electrophoretic analysis (PAGE and IEF) of whey proteins, using standard cheeses. Similar predictions of the percentages of milks from the three species were obtained when either SMLR or PCR were applied to the electrophoretic data, i.e. the optical intensity of the electrophoretic bands (PAGE or IEF) of the whey proteins. The root mean square error of prediction in cross-validation (RMSEPCV) was lower than 4% in all cases.     

Symbiosis of nurse and machine through fuzzy logic: improved specificity of a neonatal pulse oximeter alarm

This article describes the theoretical underpinnings that preceded the design of a new neonatal pulse oximeter alarm that differentiates true from false alarms based on an artificial intelligence theory called "fuzzy logic." The connection between the intuition and sense of advocacy gained through neonatal primary nursing and the application of fuzzy logic to solve the problem of false alarms--that is, the symbiosis between nurse and machine--are explained. Emphasis is placed throughout on the importance of involving nurses in the development of the technology for which they are responsible.     

Longitudinal analysis of utilization of inpatient treatment based on insurance data of mandatory health insurance

AIM: To investigate which of the routinely collected claims data from the German "Legal sickness funds" on hospital utilisation may be used, in addition to that prescribed by the legislator. DESIGN: We used claims data to study a cohort of sickness fund beneficiaries who were insured during the complete year 1992 (n = 81,309). Six utilisation parameters, using the number of cases and in hospital days overall as well as diseases specific (i.e. readmission rates, in-hospital days per person with [at least] one hospital stay) were calculated. RESULTS: There are 88 persons with (at least) one hospital stay, 116 hospital cases and a total of 1306 in-hospital days per 1000 insured persons in the study cohort. The average hospital days per person (14.8 days) are ca. 30% higher than the average length of stay (11.2 days). Hospital utilisation increases with age. Hospital stays associated with ICD-239 (neoplasms of unknown origin) resulted in a higher than average number of hospital days in total although the mean length of stay is not above the average. This is due to a high readmission rate. Hospital stays associated with elective surgical procedures have a high prevalence rate but a low readmission ratio and short length of stay. CONCLUSION: The parameters related to insured persons, cases and specifically personal parameters of hospital utilisation allow a detailed analysis of hospital care; different utilisation and user patterns can be investigated and possible determinants of utilisation can be identified. After technical transformation, routine data of the sickness funds can be used to obtain information relevant for health care planners as well as for quality management.