An adaptive group sequential design for phase II/III clinical trials that select a single treatment from several

There is increasing interest in combining Phases II and III of clinical development into a single trial in which one of a small number of competing experimental treatments is ultimately selected and where a valid comparison is made between this treatment and the control treatment. Such a trial usually proceeds in stages, with the least promising experimental treatments dropped as soon as possible. In this paper we present a highly flexible design that uses adaptive group sequential methodology to monitor an order statistic. By using this approach, it is possible to design a trial which can have any number of stages, begins with any number of experimental treatments, and permits any number of these to continue at any stage. The test statistic used is based upon efficient scores, so the method can be easily applied to binary, ordinal, failure time, or normally distributed outcomes. The method is illustrated with an example, and simulations are conducted to investigate its type I error rate and power under a range of scenarios.

The distributed work of local action: interaction amongst virtually collocated research teams

Existing research on synchronous remote working in CSCW has highlighted the troubles that can arise because actions at one site are (partially) unavailable to remote colleagues. Such ‘local action’ is routinely characterised as a nuisance, a distraction, subordinate and the like. This paper explores interconnections between ‘local action’ and ‘distributed work’ in the case of a research team virtually collocated through ‘MiMeG’. MiMeG is an e-Social Science tool that facilitates ‘distributed data sessions’ in which social scientists are able to remotely collaborate on the real-time analysis of video data. The data are visible and controllable in a shared workspace and participants are additionally connected via audio conferencing. The findings reveal that whilst the (partial) unavailability of local action is at times problematic, it is also used as a resource for coordinating work. The paper considers how local action is interactionally managed in distributed data sessions and concludes by outlining implications of the analysis for the design and study of technologies to support group-to-group collaboration.

Prediction of coagulation properties, titratable acidity and pH of bovine milk using mid-infrared spectroscopy

This study investigated the potential application of mid-infrared spectroscopy (MIR 4,000–900 cm−1) for the determination of milk coagulation properties (MCP), titratable acidity (TA), and pH in Brown Swiss milk samples (n = 1,064). Because MCP directly influence the efficiency of the cheese-making process, there is strong industrial interest in developing a rapid method for their assessment. Currently, the determination of MCP involves time-consuming laboratory-based measurements, and it is not feasible to carry out these measurements on the large numbers of milk samples associated with milk recording programs. Mid-infrared spectroscopy is an objective and nondestructive technique providing rapid real-time analysis of food compositional and quality parameters. Analysis of milk rennet coagulation time (RCT, min), curd firmness (a30, mm), TA (SH°/50 mL; SH° = Soxhlet-Henkel degree), and pH was carried out, and MIR data were recorded over the spectral range of 4,000 to 900 cm−1. Models were developed by partial least squares regression using untreated and pretreated spectra. The MCP, TA, and pH prediction models were improved by using the combined spectral ranges of 1,600 to 900 cm−1, 3,040 to 1,700 cm−1, and 4,000 to 3,470 cm−1. The root mean square errors of cross-validation for the developed models were 2.36 min (RCT, range 24.9 min), 6.86 mm (a30, range 58 mm), 0.25 SH°/50 mL (TA, range 3.58 SH°/50 mL), and 0.07 (pH, range 1.15). The most successfully predicted attributes were TA, RCT, and pH. The model for the prediction of TA provided approximate prediction (R2 = 0.66), whereas the predictive models developed for RCT and pH could discriminate between high and low values (R2 = 0.59 to 0.62). It was concluded that, although the models require further development to improve their accuracy before their application in industry, MIR spectroscopy has potential application for the assessment of RCT, TA, and pH during routine milk analysis in the dairy industry. The implementation of such models could be a means of improving MCP through phenotypic-based selection programs and to amend milk payment systems to incorporate MCP into their payment criteria.

eRules: a modular adaptive classification rule learning algorithm for data streams

Advances in hardware and software in the past decade allow to capture, record and process fast data streams at a large scale. The research area of data stream mining has emerged as a consequence from these advances in order to cope with the real time analysis of potentially large and changing data streams. Examples of data streams include Google searches, credit card transactions, telemetric data and data of continuous chemical production processes. In some cases the data can be processed in batches by traditional data mining approaches. However, in some applications it is required to analyse the data in real time as soon as it is being captured. Such cases are for example if the data stream is infinite, fast changing, or simply too large in size to be stored. One of the most important data mining techniques on data streams is classification. This involves training the classifier on the data stream in real time and adapting it to concept drifts. Most data stream classifiers are based on decision trees. However, it is well known in the data mining community that there is no single optimal algorithm. An algorithm may work well on one or several datasets but badly on others. This paper introduces eRules, a new rule based adaptive classifier for data streams, based on an evolving set of Rules. eRules induces a set of rules that is constantly evaluated and adapted to changes in the data stream by adding new and removing old rules. It is different from the more popular decision tree based classifiers as it tends to leave data instances rather unclassified than forcing a classification that could be wrong. The ongoing development of eRules aims to improve its accuracy further through dynamic parameter setting which will also address the problem of changing feature domain values.

Improved likelihood inference for the shape parameter in Weibull regression

We obtain adjustments to the profile likelihood function in Weibull regression models with and without censoring. Specifically, we consider two different modified profile likelihoods: (i) the one proposed by Cox and Reid [Cox, D.R. and Reid, N., 1987, Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society B, 49, 1-39.], and (ii) an approximation to the one proposed by Barndorff-Nielsen [Barndorff-Nielsen, O.E., 1983, On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70, 343-365.], the approximation having been obtained using the results by Fraser and Reid [Fraser, D.A.S. and Reid, N., 1995, Ancillaries and third-order significance. Utilitas Mathematica, 47, 33-53.] and by Fraser et al. [Fraser, D.A.S., Reid, N. and Wu, J., 1999, A simple formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 655-661.]. We focus on point estimation and likelihood ratio tests on the shape parameter in the class of Weibull regression models. We derive some distributional properties of the different maximum likelihood estimators and likelihood ratio tests. The numerical evidence presented in the paper favors the approximation to Barndorff-Nielsen`s adjustment.

En jämförelse av molnbaserade realtidsanalystjänster : Skillnader i användbarhet mellan multi-tenant och single-tenant arkitekturer

Internet of Things är ett samlingsbegrepp för den utveckling som innebär att olika typer av enheter kan förses med sensorer och datachip som är uppkopplade mot internet. En ökad mängd data innebär en ökad förfrågan på lösningar som kan lagra, spåra, analysera och bearbeta data. Ett sätt att möta denna förfrågan är att använda sig av molnbaserade realtidsanalystjänster. Multi-tenant och single-tenant är två typer av arkitekturer för molnbaserade realtidsanalystjänster som kan användas för att lösa problemen med hanteringen av de ökade datamängderna. Dessa arkitekturer skiljer sig åt när det gäller komplexitet i utvecklingen. I detta arbete representerar Azure Stream Analytics en multi-tenant arkitektur och HDInsight/Storm representerar en single-tenant arkitektur. För att kunna göra en jämförelse av molnbaserade realtidsanalystjänster med olika arkitekturer, har vi valt att använda oss av användbarhetskriterierna: effektivitet, ändamålsenlighet och användarnöjdhet. Vi kom fram till att vi ville ha svar på följande frågor relaterade till ovannämnda tre användbarhetskriterier: • Vilka likheter och skillnader kan vi se i utvecklingstider? • Kan vi identifiera skillnader i funktionalitet? • Hur upplever utvecklare de olika analystjänsterna? Vi har använt en design and creation strategi för att utveckla två Proof of Concept prototyper och samlat in data genom att använda flera datainsamlingsmetoder. Proof of Concept prototyperna inkluderade två artefakter, en för Azure Stream Analytics och en för HDInsight/Storm. Vi utvärderade dessa genom att utföra fem olika scenarier som var för sig hade 2-5 delmål. Vi simulerade strömmande data genom att låta en applikation kontinuerligt slumpa fram data som vi analyserade med hjälp av de två realtidsanalystjänsterna. Vi har använt oss av observationer för att dokumentera hur vi arbetade med utvecklingen av analystjänsterna samt för att mäta utvecklingstider och identifiera skillnader i funktionalitet. Vi har även använt oss av frågeformulär för att ta reda på vad användare tyckte om analystjänsterna. Vi kom fram till att Azure Stream Analytics initialt var mer användbart än HDInsight/Storm men att skillnaderna minskade efter hand. Azure Stream Analytics var lättare att arbeta med vid simplare analyser medan HDInsight/Storm hade ett bredare val av funktionalitet.

Modelagem de dados de falhas de equipamentos de sub-superfície em poços de petróleo da Bacia Potiguar

This master´s thesis presents a reliability study conducted among onshore oil fields in the Potiguar Basin (RN/CE) of Petrobras company, Brazil. The main study objective was to build a regression model to predict the risk of failures that impede production wells to function properly using the information of explanatory variables related to wells such as the elevation method, the amount of water produced in the well (BSW), the ratio gas-oil (RGO), the depth of the production bomb, the operational unit of the oil field, among others. The study was based on a retrospective sample of 603 oil columns from all that were functioning between 2000 and 2006. Statistical hypothesis tests under a Weibull regression model fitted to the failure data allowed the selection of some significant predictors in the set considered to explain the first failure time in the wells

Estimação em modelos de tempo de falha acelerado para dados de sobrevivência correlacionados

We presented in this work two methods of estimation for accelerated failure time models with random e_ects to process grouped survival data. The _rst method, which is implemented in software SAS, by NLMIXED procedure, uses an adapted Gauss-Hermite quadrature to determine marginalized likelihood. The second method, implemented in the free software R, is based on the method of penalized likelihood to estimate the parameters of the model. In the _rst case we describe the main theoretical aspects and, in the second, we briey presented the approach adopted with a simulation study to investigate the performance of the method. We realized implement the models using actual data on the time of operation of oil wells from the Potiguar Basin (RN / CE).

Predição em modelos de tempo de falha acelerado com efeito aleatório para avaliação de riscos de falha em poços petrolíferos

We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance.

Effect of whitening agents on dentin bonding

Background: Several studies have shown a reduction in enamel bond strengths when the bonding procedure is carried out immediately after vital bleaching with peroxides. This reduction in bond strengths has become a concern in cosmetic dentistry with the introduction of new in-office and waiting-room bleaching techniques. The aim of this in vitro study was to evaluate the effect of three bleaching regimens: 35% hydrogen peroxide (HP), 35% carbamide peroxide (CP), and 10% CP, on dentin bond strengths. Materials and Methods: One hundred and twenty fresh bovine incisors were used in this study. The labial surface of each tooth was ground flat to expose dentin and was subsequently polished with 600-grit wet silicon carbide paper. The remaining dentin thickness was monitored and kept at an average of 2 mm. The teeth were randomly assigned to four bleaching regimens (n = 30): (A) control, no bleaching treatment; (B) 35% HP for 30 minutes; (C) 35% CP for 30 minutes; and (D) 10% CP for 6 hours. For each group, half of the specimens (n = 15) were bonded with Single Bond/Z100 immediately after the bleaching treatment, whereas the other half was bonded after the specimens were stored for 1 week in artificial saliva at 37°C. The specimens were fractured in shear using an Instron machine. Results: For the groups bonded immediately after bleaching, one-way analysis of variance (ANOVA) followed by the Duncan's post hoc test revealed a statistically significant reduction in bond strengths in a range from 71% to 76%. For the groups bonded at 1 week, one-way ANOVA showed that group B (35% HP for 30 min) resulted in the highest bond strengths, whereas 10% CP resulted in the lowest bond strengths. Student's t-test showed that delayed bonding resulted in a significant increase in bond strengths for groups B (35% HP) and C (35% CP); whereas the group bleached with 10% CP (group D) remained in the same range obtained for immediate bonding. Storage in artificial saliva also affected the control group, reducing its bond strengths to 53% of the original. ©2000 BC Decker Inc.

Effect of Surface Treatments on the Bond Strength between Composite Resin and Acrylic Resin Denture Teeth

Purpose: This investigation studied the effects of 3 surface treatments on the shear bond strength of a light-activated composite resin bonded to acrylic resin denture teeth. Materials and Methods: The occlusal surfaces of 30 acrylic resin denture teeth were ground flat with up to 400-grit silicon carbide paper. Three different surface treatments were evaluated: (1) the flat ground surfaces were primed with methyl methacrylate (MMA) monomer for 180 seconds; (2) light-cured adhesive resin was applied and light polymerized according to the manufacturer's instructions; and (3) treatment 1 followed by treatment 2. The composite resin was packed on the prepared surfaces using a split mold. The interface between tooth and composite was loaded at a cross-head speed of 0.5 mm/min until failure. Results: Analysis of variance indicated significant differences between the surface treatments. Results of mean comparisons using Tukey's test showed that significantly higher shear bond strengths were developed by bonding composite resin to the surfaces that were previously treated with MMA and then with the bonding agent when compared to the other treatments. Conclusion: Combined surface treatment of MMA monomer followed by application of light-cured adhesive resin provided the highest shear bond strength between composite resin and acrylic resin denture teeth.

The influence of chemical activation on hardness of dual-curing resin cements.

During the cementation of metallic restorations, the polymerization of dual-curing resin cements depends exclusively on chemical activation. This study evaluated the influence of chemical activation compared with dual-curing (chemical and light activation), on the hardness of four dual-curing resin cements. In a darkened environment, equal weight proportions of base and catalyst pastes of the cements Scotchbond Resin Cement, Variolink II, Enforce and Panavia F were mixed and inserted into moulds with cavities of 4 mm in diameter and 2 mm in height. Subsequently, the cements were: 1) not exposed to light (chemical activation = self-cured groups) or 2) photoactivated (dual-curing = dual-cured groups). The Vickers hardness number was measured at 1 hour, 24 hours and 7 days after the start time of cements' spatulation. For all the cements, the hardness values of self-cured groups were lower than those of the respective dual-cured groups at 1 hour and 24 hours. At 7 days, this behavior continued for Variolink II and Panavia F, whilst for Scotchbond Resin Cement and Enforce there was no statistical difference between the two activation modes. All cements showed a significant increase in their hardness values from 1 hour to 7 days for both activation modes. Of the self-cured groups, Scotchbond Resin Cement and Variolink II presented the highest and the lowest hardness values, respectively, for all three times tested. Within the limitations of this study, up to the time of 24 h, chemical activation alone was unable to promote similar hardness as to that obtained with dual-curing.

The relationship between onset of blood lactate accumulation, critical velocity, and maximal lactate steady state in soccer players

The objective of this study was to analyze the validity of the velocity corresponding to the onset of blood lactate accumulation (OBLA) and critical velocity (CV) to determine the maximal lactate steady state (MLSS) in soccer players. Twelve male soccer players (21.5 ± 1.0 years) performed an incremental treadmill test for the determination of OBLA. The velocity corresponding to OBLA (3.5 mM of blood lactate) was determined through linear interpolation. The subjects returned to the laboratory on 7 occasions for the determination of MLSS and CV. The MLSS was determined from 5 treadmill runs of up to 30-minute duration and defined as the highest velocity at which blood lactate did not increase by more than 1 mM between minutes 10 and 30 of the constant velocity runs. The CV was determined by 2 maximal running efforts of 1,500 and 3,000 m performed on a 400-m running track. The CV was calculated as the slope of the linear regression of distance run versus time. Analysis of variance revealed no significant differences between OBLA (13.6 ± 1.4 km·h-1) and MLSS (13.1 ± 1.2 km·h-1) and between OBLA and CV (14.4 ± 1.1 km·h-1). The CV was significantly higher than the MLSS. There was a significant correlation between MLSS and OBLA (r = 0.80), MLSS and CV (r = 0.90), and OBLA and CV (r = 0.80). We can conclude that the OBLA can be utilized in soccer players to estimate the MLSS. In this group of athletes, however, CV does not represent a sustainable steady-state exercise intensity. © 2005 National Strength & Conditioning Association.

Effect of the association of nystatin with a tissue conditioner on its ultimate tensile strength

Purpose: This study evaluated the ultimate tensile strength of a tissue conditioner without nystatin incorporation (GI - control group) and the same tissue conditioner modified by the addition of nystatin in two concentrations: GII - 500,000 International Units (U) and GIII - 1,000,000 U, in which each milligram of the medicament corresponded to 6079 U. Materials and Methods: Dumbbell-shaped specimens (N = 7) with a central cross-sectional area of 33 × 6 × 3 mm were produced for the three experimental groups. After polymerization following manufacturer's instructions, specimens were immersed in distilled water at 37°C for either 24 hours or 7 days and then tested in tension in the MTS 810 at 40 mm/minute. Data were analyzed by two-way ANOVA followed by Tukey's test, at 95% level of confidence. Results: The means (force-grams (gf) ± standard deviation) of the ultimate tensile strength were: GI - 634.29 ± 122.80; GII - 561.92 ± 133.56; and GIII - 547.30 ± 73.47 for 24-hour storage, and GI - 536.68 ± 54.71; GII - 467.50 ± 143.51; and GIII - 500.62 ± 159.76 for 7-day storage. There were no statistically significant differences among the three experimental groups (p > 0.05). The ultimate tensile strength means of all experimental groups after 7 days were significantly lower than those observed after 24 hours (p = 0.04). Conclusions: The results of this study suggest that the addition of nystatin into the tissue conditioner investigated in concentrations below 1,000,000 U did not affect its ultimate tensile strength. Copyright © 2006 by The American College of Prosthodontists.

Diametral tensile strength of dual-curing resin cements submitted exclusively to autopolymerization.

OBJECTIVES: To evaluate, at different times, the diametral tensile strength (DTS) of dual-curing resin cements that were not photopolymerized. METHOD AND MATERIALS: Equal amounts of base and catalyst pastes of Panavia F (Kuraray), Variolink II (Vivadent), Rely X (3M ESPE), and Enforce (Dentsply) were mixed and inserted into cylindrical molds (4 x 2 mm) (n = 10). Cements were not photopolymerized. DTS test was performed in a testing machine at 30 minutes, 1 hour, 24 hours, and 7 days. The specimens were stored in light-proof containers with distilled water at 37 degrees C until the time of assay. An autopolymerizing resin cement (Cement-It, Jeneric Pentron) and a zinc phosphate cement served as controls. One-way analysis of variance (ANOVA) and Tukey test were performed separately for each cement and for each time (P <.05). RESULTS: All cements showed an increase in DTS when tested at 1 and 24 hours. Tests at 24 hours and 7 days revealed no statistically significant differences. In all groups, the zinc phosphate cement had the lowest DTS mean values (2.1 MPa, 3.6 MPa, 6.5 MPa, and 6.9 MPa), while Cement-It (35.1 MPa, 33.6 MPa, 46.9 MPa, and 46.3 MPa) and Enforce (31.9 MPa, 31.7 MPa, 43.4 MPa, and 47.6 MPa) presented the highest DTS mean values. CONCLUSION: All cements presented maximal strength at 24 hours. The dual-curing resin cements, even when nonphotopolymerized, demonstrated higher DTS than the zinc phosphate cement and similar or lower values than the autopolymerizing resin cement.