MI Method Research Articles

CuO/CeO2 catalysts prepared by modified impregnation method for ethyl acetate oxidation

The impregnation method is one of the most popular methods for preparing various types of supported catalysts. However, the preparation of highly active catalysts by the conventional impregnation method is still a great challenge. In this paper, a modified impregnation method (MI) was developed to prepare CuO/CeO2 catalysts for the catalytic oxidation of ethyl acetate (EA). It was found that the 5 %CuO/CeO2 catalyst (5-MI-500) prepared by MI method achieves 100% EA conversion at a low temperature of 200 °C. However, the temperature for 100% EA conversion over the 5 %CuO/CeO2 catalyst prepared by the conventional method is as high as 300 °C. Notably, the 5-MI-500 catalyst exhibits the highest proportion of well-dispersed CuO and Cu-O-Ce structures, which synergistically enhance catalyst activity. The well-dispersed CuO particles enhance the redox ability of the catalyst, while the Cu-O-Ce structure provides high activated oxygen via oxygen vacancy and better thermal stability during catalytic reaction. Accordingly, the possible reaction mechanism over the 5-MI-500 catalyst for EA oxidation was proposed. This study demonstrates that the MI method reported in this paper can provide a feasible methodology to prepare highly active catalysts with unique structures.

395 Assessing imputation methods with the lebrikizumab clinical trial program

Abstract Missing data occur in clinical trials and have the potential to lead to biased results. Subsequently, the analytical methods for handling the missing data are important to evaluate. In atopic dermatitis (AD) trials, missing data are not handled consistently across studies. Lebrikizumab is a monoclonal antibody that binds with high affinity and slow off-rate to interleukin (IL)-13, thereby blocking the downstream effects of IL-13 with high potency. In ADvocate1 (NCT04146363) and ADvocate2 (NCT04178967), two randomized, double-blinded, placebo-controlled Phase 3 trials evaluating the efficacy and safety of lebrikizumab monotherapy in adolescent and adult patients with moderate-to-severe AD, a combined nonresponder/multiple imputation (NRI/MI) approach, was applied on the primary and key secondary endpoints. This study aims to illustrate the NRI/MI method using individual patient examples and to present Week 16 study results from ADvocate1 and ADvocate2 with NRI/MI and single imputation methods, NRI and last-observation carried forward (LOCF). In the combined NRI/MI method, data from patients after initiating rescue medication or discontinuing treatment due to lack of efficacy were imputed with NRI, and missing data for other reasons were imputed with MI, which uses a statistical model based on all available patient data to impute missing values. The MI method considers each patient’s trajectory and leverages information from other patients within the same treatment arm to impute the missing data. With NRI alone, the cause leading to the missing data is not considered and missing data for any reason are imputed as nonresponse. With LOCF, missing data are replaced with the last available measurement; LOCF assumes that the patient response would be stable over time and does not consider the reason for missing data. We determined the amount of missing data in ADvocate1 and ADvocate2, and we assessed patient-level imputed IGA scores to illustrate NRI/MI, NRI and LOCF. With these missing data handling methods, we evaluated the percentage of patients achieving the co-primary endpoints of ADvocate1 and ADvocate2: an Investigator’s Global Assessment score of 0 or 1 [IGA (0,1); clear or almost clear] with ≥2-point improvement from baseline or 75% improvement in Eczema Area and Severity Index (EASI 75) at Week 16. With the NRI/MI method, most missing data at Week 16 were imputed with NRI (ADvocate1: 73%, ADvocate2: 82%) compared with MI (ADvocate1: 27%, ADvocate2: 18%). Example imputed IGA scores based on patient-level data will be presented to demonstrate the missing data handling methods. For NRI/MI, NRI and LOCF, respectively, the percentage of patients achieving IGA 0,1 were 12.7%, 11.3% and 12.8% for placebo in ADvocate1 and 10.8%, 9.6% and 11.0% for placebo in ADvocate2; 43.1%, 41.0% and 42.4% for lebrikizumab in ADvocate1 and 33.2%, 31.3% and 33.5% for lebrikizumab in ADvocate2. The percentage of patients achieving EASI 75 were 16.2%, 14.2% and 16.3% for placebo in ADvocate1 and 18.1%, 17.1% and 19.2% for placebo in ADvocate2; 58.8%, 56.5% and 60.1% for lebrikizumab in ADvocate1 and 52.1%, 50.2% and 55.5% for lebrikizumab in ADvocate2. When using the NRI/MI method, we determined most missing data in ADvocate1 and ADvocate2 were handled with NRI. This analysis suggests that the NRI/MI method may provide a realistic estimation of response rate in ADvocate1 and ADvocate2.

A Hybrid Forecasting Model to Simulate the Runoff of the Upper Heihe River

River runoff simulation and prediction are important for controlling the water volume and ensuring the optimal allocation of water resources in river basins. However, the instability of medium- and long-term runoff series increases the difficulty of runoff forecasting work. In order to improve the prediction accuracy, this research establishes a hybrid deep learning model framework based on variational mode decomposition (VMD), the mutual information method (MI), and a long short-term memory network (LSTM), namely, VMD-LSTM. First, the original runoff data are decomposed into a number of intrinsic mode functions (IMFs) using VMD. Then, for each IMF, a long short-term memory (LSTM) network is applied to establish the prediction model, and the MI method is used to determine the data input lag time. Finally, the prediction results of each subsequence are reconstructed to obtain the final forecast result. We explored the predictive performance of the model with regard to monthly runoff in the upper Heihe River Basin, China, and compared its performance with other single and hybrid models. The results show that the proposed model has obvious advantages in terms of the performance of point prediction and interval prediction compared to several comparative models. The Nash–Sutcliffe efficiency coefficient (NSE) of the prediction results reached 0.96, and the coverage of the interval prediction reached 0.967 and 0.908 at 95% and 90% confidence intervals, respectively. Therefore, the proposed model is feasible for simulating the monthly runoff of this watershed.

Alternating prestress monitoring of steel strands based on the magnetoelastic inductance method

Alternating prestress is difficult to measure. By analyzing the inverse magnetostriction effect and the magnetic hysteresis, a theoretical model was established to describe the prestress-inductance relationship. The results of the prestress monitoring experiment showed that the inductance was influenced by the irreversible magnetization, the plastic deformation, and the hysteresis effect. Keeping the stress range constant, the inductance range was unaffected by the number of load cycles. The inductance can be used to judge whether the prestress is reasonable. The parabolic fitting method was employed to establish the mapping from the inductance to the prestress. When the stress range was 10% design prestress or 20% design prestress, the prestress monitoring error, less than 12.56% or 18.77%, was close to the magnetoelastic method and the frequency-based method. Based on the proposed calculation method, the MI method could monitor the alternating prestress of steel strands.

Brief Motivational Interviewing Counseling to Improve Oral Hygiene Behavior Among Adolescent

Aim: To analyze the effect of the brief motivational interviewing counselling approach on the knowledge, attitudes and tooth brushing practice of adolescents. Method: This research is a quasi-experiment with a pre-test and post-test design with a control group design. The research sample was 80 adolescents aged 12 and 13 years. Respondents were divided into two groups, namely 40 intervention and control groups based on inclusion criteria. The intervention group was given the MI approach, and the control group was assigned conventional dental health education. The MI group also received follow-up over the phone. Both groups filled out knowledge and attitude questionnaires before being given treatment. Plaque index and tooth brushing practice examinations were performed at baseline and four weeks after intervention. Results: The results showed an increase in the average score of oral health knowledge, attitude, tooth brushing practice in all groups. The plaque index showed a decrease in the average score in all groups. The test of both groups showed that brief MI counseling was more effective than conventional dental health education, oral health knowledge(p=<0.001), attitude((p=<0.001), tooth brushing practice( p = 0.001), plaque index (p = 0.011). Follow-up MI by telephone in adolescents is beneficial in the research during the covid-19 pandemic as a promotive and preventive effort to improve dental health behaviour. The MI method by telephone is very interesting for adolescents, easily accessible and time-efficient. Conclusion : The MI counselling brief intervention can change dental and oral health behaviour through increasing knowledge, attitudes, tooth brushing practices and reducing the dental and oral hygiene index scores of adolescents. MI interventions need to be combined with other interventions to get more effective results for research sustainability. Keywords: Motivational Interviewing, Oral Hygiene Behaviour, Adolescent

Daily Runoff Forecasting Using Ensemble Empirical Mode Decomposition and Long Short-Term Memory

Hydrological series data are non-stationary and nonlinear. However, certain data-driven forecasting methods assume that streamflow series are stable, which contradicts reality and causes the simulated value to deviate from the observed one. Ensemble empirical mode decomposition (EEMD) was employed in this study to decompose runoff series into several stationary components and a trend. The long short-term memory (LSTM) model was used to build the prediction model for each sub-series. The model input set contained the historical flow series of the simulation station, its upstream hydrological station, and the historical meteorological element series. The final input of the LSTM model was selected by the MI method. To verify the effect of EEMD, this study used the Radial Basis Function (RBF) model to predict the sub-series, which was decomposed by EEMD. In addition, to study the simulation characteristics of the EEMD-LSTM model for different months of runoff, the GM(group by month)-EEMD-LSTM was set up for comparison. The key difference between the GM-EEMD-LSTM model and the EEMD-LSTM model is that the GM model must divide the runoff sequence on a monthly basis, followed by decomposition with EEMD and prediction with the LSTM model. The prediction results of the sub-series obtained by the LSTM and RBF exhibited better statistical performance than those of the original series, especially for the EEMD-LSTM. The overall GM-EEMD-LSTM model performance in low-water months was superior to that of the EEMD-LSTM model, but the simulation effect in the flood season was slightly lower than that of the EEMD-LSTM model. The simulation results of both models are significantly improved compared to those of the LSTM model.

Notice of Removal: Substation Grounding Studies with More Accurate Fault Simulation Strategy and SI / MI Method

Notice of Removal: Substation Grounding Studies with More Accurate Fault Simulation Strategy and SI / MI Method

Motivational Interviewing in the Reciprocal Engagement Model of Genetic Counseling: a Method Overview and Case Illustration.

Motivational Interviewing is a well-described counseling method that has been applied to a broad range of health behavior encounters. Genetic counseling is an emerging area of utilization for the method of Motivational Interviewing. The relational and technical elements of the MI method are described within the context of genetic counseling encounters. Case excerpts will be used to illustrate incorporation of MI methods into the Reciprocal Engagement Model of the genetic counseling encounter.

Comparisons of Three Empirical Methods for Partial Factorial Invariance: Forward, Backward, and Factor-Ratio Tests

When factorial invariance is violated, a possible first step in locating the source of violation(s) might be to pursue partial factorial invariance (PFI). Two commonly used methods for PFI are sequential use of the modification index (backward MI method) and the factor-ratio test. In this study, we propose a simple forward method using the confidence interval (forward CI method). We compare the performances of the aforementioned 3 methods under various simulated PFI conditions. Results indicate that the forward CI method using 99% CIs has the highest perfect recovery rates and the lowest Type I error rates. A performance that is competitive with this is that produced by the backward method with the more conservative criterion (MI = 6.635). Consistently delivering the poorest performance, regardless of the chosen confidence level, was the factor-ratio test. Also discussed are the work’s contribution, implications, and limitations.

Biofabrication of zinc oxide nanoparticles using fruit extract of Rosa canina and their toxic potential against bacteria: A mechanistic approach

The use of plant extract in the biosynthesis of nanoparticles (NPs) can be an eco-friendly approach and have been suggested as a possible alternative to classic methods namely physical and chemical procedures. In this study, the biosynthesis of zinc oxide (ZnO) NPs by both “conventional heating” (CH) and “microwave irradiation” (MI) methods has been reported. Stable and spherical ZnONPs were produced using zinc nitrate and flesh extract of Rosa canina fruit (rosehip) which was used as a precursor. The flesh extract acts as a reducing and capping agent for generation of ZnONPs. The structural, morphological and colloidal properties of the as-synthesized NPs have been confirmed by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy Dispersive X-ray (EDX), Fourier transform Infrared (FT-IR) and Dynamic Light Scattering (DLS). In comparison with the CH method, the MI method has some advantages such as significantly short reaction time (within 8min) owing to the high heating rate and thus the accelerated reaction rate. Both methods led to the synthesis of nearly identical NPs with respect to shape and size according to the results of DLS, XRD and SEM techniques. The possible mechanism for synthesis pathway has been proposed based on FT IR results, XRD patterns, potentiometric data and antioxidant activity. In addition, the antibacterial activity of as-prepared ZnONPs was investigated against several bacteria such as Listeria monocytogenes, Escherichia coli, Salmonella typhimurium. Moreover, the efficacy of ZnONPs to treat cancer cell lines were measured by means of cell viability test via MTT assay in which concentrations of 0.05 and 0.1mg/mL of ZnONPs induced a very low toxicity. Thus, the present investigation reveals that ZnONPs have the potential for various medical and industrial applications.

SAR 영상 자동정합을 위한 영상정합기법의 비교연구

SAR satellite can acquire clear imagery regardless of weather and the images are widely used for land management, natural hazard monitoring and many other applications. Automatic image matching technique is necessary for management of a huge amount of SAR data. Nevertheless, it is difficult to assure the accuracy of image matching due to the difference of image-capturing attitude and time. In this paper, we compared performances of MI method, FMT method and SIFT method by applying arbitrary displacement and rotation to TerraSAR-X images and changing resolution of the images. As a result, when the features having specific intensity were distributed well in SAR imagery, MI method could assure 0~2 pixels accuracy even if the images were captured in different geometry. But the accuracy of FMT method was significantly poor for the images having different spatial resolutions and the error was represented by tens or hundreds pixels. Moreover, the ratio of corresponding matching points for SIFT method was only 0~17% and it was difficult for SIFT method to apply to SAR images captured in different geometry.

Detection of Escherichia coli colonies on confluent plates of chromogenic media used in membrane filtration

MI agar (MI), Chromocult® Coliform agar ES (Chromocult), and DC with BCIG agar (DC) are chromogenic membrane filtration culture-based methods used to assess microbiological water quality. In this study, their ability to detect Escherichia coli colonies on confluent growth plates was determined by testing water samples containing increasing concentrations of a non-E. coli growing bacterium, Citrobacter youngae. Then, their ability to inhibit the growth of non-coliform bacteria was determined by simultaneously testing 603 well water samples. Results were compared with those obtained with mFC and Colilert® methods. Results showed that the E. coli count was difficult to determine on mFC, Chromocult and DC when non-E. coli colonies reached levels of 104colony forming units (CFU)/100mL. However, the E. coli count did not interfere with Colilert until non-E. coli colonies reached concentrations of 107CFU/100mL. No inhibition was observed with MI as E. coli colonies could be easily detected in the presence of at least 107CFU/100mL of C. youngae. Using well water samples, confluent growth plates were observed for 144, 177, and 185 of the 603 well water samples tested with the MI, Chromocult and DC methods, respectively. Among these confluent growth plates, E. coli colonies were not detected for 10, 20, and 31 water samples. However, they were detected by the mFC and/or Colilert methods. Thus, among the three methods tested, the MI method presented the lowest grow rate of atypic colonies and was the only one that presents no interference in the E. coli count.

ESTIMATION METHOD OF THE HOMODYNED K-DISTRIBUTION BASED ON THE MEAN INTENSITY AND TWO LOG-MOMENTS.

The homodyned K-distribution appears naturally in the context of random walks and provides a useful model for the distribution of the received intensity in a wide range of non-Gaussian scattering configurations, including medical ultrasonics. An estimation method for the homodyned K-distribution based on the first moment of the intensity and two log-moments (XU method), namely the X and U-statistics previously studied in the special case of the K-distribution, is proposed as an alternative to a method based on the first three moments of the intensity (MI method) or the amplitude (MA method), and a method based on the signal-to-noise ratio (SNR), the skewness and the kurtosis of two fractional orders of the amplitude (labeled RSK method). Properties of the X and U statistics for the homodyned K-distribution are proved, except for one conjecture. Using those properties, an algorithm based on the bisection method for monotonous functions was developed. The algorithm has a geometric rate of convergence. Various tests were performed to study the behavior of the estimators. It was shown with simulated data samples that the estimations of the parameters 1/α and 1/(κ + 1) of the homodyned K-distribution are preferable to the direct estimations of the clustering parameter α and the structure parameter κ (with respective relative root mean squared errors (RMSEs) of 0.63 and 0.13 as opposed to 1.04 and 4.37, when N = 1000). Tests on simulated ultrasound images with only diffuse scatterers (up to 10 per resolution cell) indicated that the XU estimator is overall more reliable than the other three estimators for the estimation of 1/α, with relative RMSEs of 0.79 (MI), 0.61 (MA), 0.53 (XU) and 0.67 (RSK). For the parameter 1/(κ + 1), the relative RMSEs were equal to 0.074 (MI), 0.075 (MA), 0.069 (XU) and 0.100 (RSK). In the case of a large number of scatterers (11 to 20 per resolution cell), the relative RMSEs of 1/α were equal to 1.43 (MI), 1.27 (MA), 1.25 (XU) and 1.33 (RSK), and the relative RMSEs of 1/(κ + 1) were equal to 0.14 (MI), 0.16 (MA), 0.17 (XU) and 0.20 (RSK). The four methods were also tested on simulated ultrasound images with a variable density of periodic scatterers to test images with a coherent component. The addition of noise on ultrasound images was also studied. Results showed that the XU estimator was overall better than the three other ones. Finally, on the simulated ultrasound images, the average computation times per image were equal to 6.0 ms (MI), 8.0 ms (MA), 6.8 ms (XU) and 500 ms (RSK). Thus, a fast, reliable, and novel algorithm for the estimation of the homodyned K-distribution was proposed.

Preparation and characterization of hydrophobic Pt–Fe catalysts with enhanced catalytic activities for interface hydrogen isotope separation

Liquid phase catalytic exchange reactions are mainly used for separation of hydrogen isotopes from liquid water. Based on the carbon-supported Pt and Pt–Fe catalysts, different hydrophobic Pt and Pt–Fe catalysts were fabricated for use in such reactions. The characterization results indicated the Pt–Fe alloy was formed in the Pt3Fe/C catalyst prepared using a citric-acid-assisted NaBH4 reduction method (CA-NaBH4). However, there were more Fe oxide species and the Fe components existed independently in the Pt3Fe/C catalyst prepared by the modified microwave-irradiated ethyl glycol reduction procedure (MI). Performance tests demonstrated that the activities of the hydrophobic Pt–Fe catalysts with appropriate Fe/Pt ratios, using the MI method, were enhanced because of the addition of Fe. In contrast, the hydrophobic Pt3Fe catalyst prepared using the CA-NaBH4 method had lower catalytic activity than pure Pt. Possible reasons were explained by reaction mechanisms of double routes of LPCE catalysis.

Neural correlates of confidence in decision making

Event Abstract Back to Event Neural correlates of confidence in decision making Marina Martinez Garcia1*, Andrea Insabato1, José L. Pardo-Vázquez2, 3, Carlos Acuña2, 3 and Gustavo Deco1, 4 1 University Pompeu Fabra, Spain 2 University of Santiago de Compostela, Spain 3 Complejo Hospitalario Universitario, Spain 4 Institució Catalana de Recerca i Estudis Avançats (ICREA), Spain Mutual information is becoming a popular tool for quantifying neural responses. We used a new MI method in order to extract information about decision confidence encoded in the firing rates of premotor cortex neurons of behaving monkeys performing a decision making task. Neural recording were made during a binary forced choice decision task. The monkeys are visually stimulated with two bars appearing sequentially and separated by a delay. The monkeys have to decide whether the second stimulus was left or right tilted respect to the first one. The neural activity recorded during the task encoded the decision taken by the monkeys. A recent model of decision confidence processes in the brain predicts that decision neurons encode implicitly also a confidence signal. In order to check whether decision neurons in premotor cortex encode also confidence in the decision we developed a new confidence information metrics (CIM) which combines two mutual informations characterizing behavioral response and test difficulty. Furthermore, we infer the significance value of this measure by using surrogates based statistical test technique. Our aim was to extract the part of neural signal purely related to confidence without the interference of the decision signals. Indeed, results show that premotor cortex decision neurons encode implicitly the confidence related to the decision. Moreover we found neurons encoding the confidence but not the choice. Furthermore, an advantage of our method is that it shows the specific interval of time in which neuron’s activity encodes the confidence. CIM demonstrated to be a very powerful tool to extract confidence signals and allowed to confirm the predictions of a theoretical model of decision confidence. Funding: Supported by European Union grant EC005-024, Spanish Research Project BFU2007-61710/BFI, European Community’s FP7/2007-2013 grant n. 214728-2. Keywords: decision-making, neural correlates Conference: XI International Conference on Cognitive Neuroscience (ICON XI), Palma, Mallorca, Spain, 25 Sep - 29 Sep, 2011. Presentation Type: Poster Presentation Topic: Poster Sessions: Decision Making, Reward Processing & Response Selection Citation: Martinez Garcia M, Insabato A, Pardo-Vázquez JL, Acuña C and Deco G (2011). Neural correlates of confidence in decision making. Conference Abstract: XI International Conference on Cognitive Neuroscience (ICON XI). doi: 10.3389/conf.fnhum.2011.207.00405 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 24 Nov 2011; Published Online: 28 Nov 2011. * Correspondence: Dr. Marina Martinez Garcia, University Pompeu Fabra, Barcelona, Spain, marina.martinez@upf.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Marina Martinez Garcia Andrea Insabato José L Pardo-Vázquez Carlos Acuña Gustavo Deco Google Marina Martinez Garcia Andrea Insabato José L Pardo-Vázquez Carlos Acuña Gustavo Deco Google Scholar Marina Martinez Garcia Andrea Insabato José L Pardo-Vázquez Carlos Acuña Gustavo Deco PubMed Marina Martinez Garcia Andrea Insabato José L Pardo-Vázquez Carlos Acuña Gustavo Deco Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Study on the thermal conductive polyoxymethylene/graphite composites

AbstractThe thermal conductive composites of polyoxymethylene (POM)/graphite were prepared through four intercalation methods, including melt (MI), solution (SM), pan milling (SMI), and in situ intercalation (IM). For the purpose of improving the interfacial compatibility of POM/graphite, realizing the exfoliation and nano‐dispersion of graphite in POM matrix, the effect of the type and the content of the graphite, the nature of the coupling agents used in graphite modification on the properties of the composites was studied. The results showed that the thermal conductive properties of POM were improved remarkably from the value of 0.36 W/(m K) for neat POM to the value of 1.15 W/(m K) in presence of 30 wt % graphite, and the composites filled with the coupling agent T‐1 or T‐2 surface‐modified colloidal graphite displayed better thermal conductivity. The degree of layers exfoliation of the graphite was enhanced in the order of MI, SM, SMI, and IM. And the composites prepared by SM, SMI, and IM methods presented much more decreased size, more narrow size distribution, thinner overlapped sheets, and better dispersion of the graphite than that prepared by MI method. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2009

Computer-assisted surveillance for detecting clonal outbreaks of nosocomial infection.

Whole-house surveillance for healthcare-associated infection is no longer the recommended practice because of the large personnel time investment required. We developed a computer-based tracking system using microbiologic data as an aid in detecting potential outbreaks of healthcare-associated infections on a hospital-wide basis. Monthly total isolates of 25 clinically significant hospital pathogens were tallied from 1991 to 1998 to form a database for future comparison. Two different algorithm tools (based on increases of organism numbers over baseline) were applied to determine alert thresholds for suspected outbreaks using this information. The first algorithm (2SD) defined an alert as two standard deviations above the mean monthly number of isolates. The second (MI) defined an alert as either a 100% increase from the baseline organism number over 2 months or a >/=50% increase (compared to baseline) during a three-consecutive-month period. These two methods were compared to standard infection control professional surveillance (ICP) for the detection of clonal outbreaks over 12 months. Overall, a total of seven clonal outbreaks were detected during the 1-year study. Using standard methods, ICP investigated nine suspected outbreaks, four of which were associated with clonal microbes. The 2SD method signaled a suspected outbreak 15 times, of which three were clonal and ICP had detected one. The MI method signaled a suspected outbreak 30 times; four of these were clonal, and ICP had detected one. The sensitivity and specificity values for ICP, 2SD, and MI for detecting clonal outbreaks were 57, 43, and 57% and 17, 83, and 67%, respectively. Statistical methods applied to clinical microbiology laboratory information system data efficiently supplement infection control efforts for outbreak detection.

A ‘moving index’ method for the solution of the American options valuation problem

We introduce a new technique for the solution of the American options valuation problem, which resembles the moving boundary behavior of the solution, and thus, we call it the ‘moving index’ (MI) method. We use the so-called linear complementarity formulation of the problem for which projected successive over relaxation (PSOR) is a leading and well-known method. We report on experimental results, which demonstrate that our MI method presents dramatic improvements over PSOR since it is several times faster for a given desired accuracy. There are also cases in which the MI method continues to perform well, while it is impossible to achieve the desired accuracy with PSOR within a decent time interval.

Hartree–Fock limit properties of the water dimer in absence of BSSE

A series of calculations has been accomplished employing uncontracted even tempered basis set expansions of increasing dimension. The SCF–MI (self-consistent field for molecular interactions) binding energy and force constant for the O–H stretching involved in the hydrogen bond of the water dimer system in the limit of very extended basis set have been computed. The most extended even tempered basis set (548 functions) included diffuse f gaussian functions on oxygen and d functions on hydrogen. The effect of functions with higher angular momentum has been investigated by a different scheme. The basis set superposition error (BSSE) was avoided in an a priori fashion by applying the SCF–MI method. Bader analysis showed that the amount of charge transferred between the interacting units agrees with that computed by standard SCF supermolecule wave functions. The geometry of the system was optimised using the algorithm implemented into GAMESS-US program based on analytic first derivatives of the SCF–MI energy. The resulting SCF–MI interaction energy was estimated to be −3.45 kcal/mol, in close accordance with recently reported values. The calculated Hartree–Fock limit for the water monomer was −76.0676 au to be compared with the previous value of −76.0675 au.