Optimization of Cement Grouts Containing Silica Fume and Viscosity Modifying Admixture

There is an increasing need to identify the effect of mix composition on the rheological properties of cementitious grouts using minislump, Marsh cone, cohesion plate, washout test, and cubes to determine the fluidity, the cohesion, and other mechanical properties of grouting applications. Mixture proportioning involves the tailoring of several parameters to achieve adequate fluidity, cohesion, washout resistance and compressive strength. This paper proposes a statistical design approach using a composite fractional factorial design which was carried out to model the influence of key parameters on the performance of cement grouts. The responses relate to performance included minislump, flow time using Marsh cone, cohesion measured by Lombardi plate meter, washout mass loss and compressive strength at 3, 7, and 28 days. The statistical models are valid for mixtures with water-to-binder ratio of 0.37–0.53, 0.4–1.8% addition of high-range water reducer (HRWR) by mass of binder, 4–12% additive of silica fume as replacement of cement by mass, and 0.02–0.8% addition of viscosity modifying admixture (VMA) by mass of binder. The models enable the identification of underlying factors and interactions that influence the modeled responses of cement grout. The comparison between the predicted and measured responses indicated good accuracy of the established models to describe the effect of the independent variables on the fluidity, cohesion, washout resistance and the compressive strength. This paper demonstrates the usefulness of the models to better understand trade-offs between parameters. The multiparametric optimization is used to establish isoresponses for a desirability function for cement grout. An increase of HRWR led to an increase of fluidity and washout, a reduction in plate cohesion value, and a reduction in the Marsh cone time. An increase of VMA demonstrated a reduction of fluidity and the washout mass loss, and an increase of Marsh cone time and plate cohesion. Results indicate that the use of silica fume increased the cohesion plate and Marsh cone, and reduced the minislump. Additionally, the silica fume improved the compressive strength and the washout resistance.

A statistical framework for the design of microarray experiments and effective detection of differential gene expression

Motivation: Microarray experiments generate a high data volume. However, often due to financial or experimental considerations, e.g. lack of sample, there is little or no replication of the experiments or hybridizations. These factors combined with the intrinsic variability associated with the measurement of gene expression can result in an unsatisfactory detection rate of differential gene expression (DGE). Our motivation was to provide an easy to use measure of the success rate of DGE detection that could find routine use in the design of microarray experiments or in post-experiment assessment.

Statistical modelling of cement slurries for self compacting SIFCON containing silica fume

This paper reports a study carried out to develop a self-compacting fibre reinforced concrete containing a high fibre content with slurry infiltrated fibre concrete (SIFCON). The SIFCON was developed with 10% of steel fibres which are infiltrated by self-compacting cement slurry without any vibration. Traditionally, the infiltration of the slurry into the layer of fibres is carried out under intensive vibration. A two-level fractional factorial design was used to optimise the properties of cement-based slurries with four independent variables, such as dosage of silica fume, dosage of superplasticiser, sand content, and water/cement ratio (W/C). Rheometer, mini-slump test, Lombardi plate cohesion meter, J-fibre penetration test, and induced bleeding were used to assess the behaviour of fresh cement slurries. The compressive strengths at 7 and 28 days were also measured. The statistical models are valid for slurries made with W/C of 0.40 to 0.50, 50 to 100% of sand by mass of cement, 5 to 10% of silica fume by mass of cement, and SP dosage of 0.6 to 1.2% by mass of cement. This model makes it possible to evaluate the effect of individual variables on measured parameters of fresh cement slurries. The proposed models offered useful information to understand trade-offs between mix variables and compare the responses obtained from various test methods in order to optimise self-compacting SIFCON.

Applications of statistical models in proportioning medium strength self-compacting concrete

Self-compacting concrete (SCC) is generally designed with a relatively higher content of finer, which includes cement, and dosage of superplasticizer than the conventional concrete. The design of the current SCC leads to high compressive strength, which is already used in special applications, where the high cost of materials can be tolerated. Using SCC, which eliminates the need for vibration, leads to increased speed of casting and thus reduces labour requirement, energy consumption, construction time, and cost of equipment. In order to obtain and gain maximum benefit from SCC it has to be used for wider applications. The cost of materials will be decreased by reducing the cement content and using a minimum amount of admixtures. This paper reviews statistical models obtained from a factorial design which was carried out to determine the influence of four key parameters on filling ability, passing ability, segregation and compressive strength. These parameters are important for the successful development of medium strength self-compacting concrete (MS-SCC). The parameters considered in the study were the contents of cement and pulverised fuel ash (PFA), water-to-powder ratio (W/P), and dosage of superplasticizer (SP). The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined to Orimet, JRing combined to cone, fresh segregation, and compressive strength at 7, 28 and 90 days. The models are valid for mixes made with 0.38 to 0.72 W/P ratio, 60 to 216 kg/m3 of cement content, 183 to 317 kg/m3 of PFA and 0 to 1% of SP, by mass of powder. The utility of such models to optimize concrete mixes to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mix parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined to Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show trade-offs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixes. The paper establishes the usefulness of the mathematical models as a tool to facilitate the test protocol required to optimise medium strength SCC.

Design, characterisation and preliminary clinical evaluation of a novel mucoadhesive topical formulation containing tetracycline for the treatment of periodontal disease

This study describes the formulation, characterisation and preliminary clinical evaluation of mucoadhesive, semi-solid formulations containing hydroxyethylcellulose (HEC, 1-5%, w/w), polyvinylpyrrolidine (PVP, 2 or 3%, w/w), poly carbophil (PC, 1 or 3%, w/w) and tetracycline (5%, w/w, as the hydrochloride). Each formulation was characterised in terms of drug release, hardness, compressibility, adhesiveness (using a texture analyser in texture profile analysis mode), syringeability (using a texture analyser in compression mode) and adhesion to a mucin disc (measured as a detachment force using the texture analyser in tensile mode). The release exponent for the formulations ranged from 0.78+/-0.02 to 1.27+/-0.07, indicating that drug release was non-diffusion controlled. Increasing the concentrations of each polymeric component significantly increased the time required for 10 and 30% release of the original mass of tetracycline, due to both increased viscosity and, additionally, the unique swelling properties of the formulations. Increasing concentrations of each polymeric component also increased the hardness, compressibility, adhesiveness, syringeability and mucoadhesion of the formulations. The effects on product hardness, compressibility and syringeability may be due to increased product viscosity and, hence, increased resistance to compression. Similarly, the effects of these polymers on adhesiveness/mucoadhesion highlight their mucoadhesive nature and, importantly, the effects of polymer state (particularly PC) on these properties. Thus, in formulations where the neutralisation of PC was maximally suppressed, adhesiveness and mucoadhesion were also maximal. Interestingly, statistical interactions were primarily observed between the effects of HEC and PC on drug release, mechanical and mucoadhesive properties. These were explained by the effects of HEC on the physical state of PC, namely swollen or unswollen. In the preliminary clinical evaluation, a formulation was selected that offered an appropriate balance of the above physical properties and contained 3% HEC, 3% PVP and 1% PC, in addition to tetracycline 5% (as the hydrochloride). The clinical efficacy of this (test) formulation was compared to an identical tetracycline-devoid (control) formulation in nine periodontal pockets (greater than or equal to 5 mm depth). One week following administration of the test formulation, there was a significant improvement in periodontal health as identified by reduced numbers of sub-gingival microbial pathogens. Therefore, it can be concluded that, when used in combination with mechanical plaque removal, the tetracycline-containing semi-solid systems described in this study would augment such therapy by enhancing the removal of pathogens, thus improving periodontal health. (C) 2000 Elsevier Science B.V. All rights reserved.

Factorial Design of Cement Slurries Containing Limestone Powder for Self-Consolidating Slurry-Infiltrated Fiber Concrete

Slurries with high penetrability for production of Self-consolidating Slurry Infiltrated Fiber Concrete (SIFCON) were investigated in this study. Factorial experimental design was adopted in this investigation to assess the combined effects of five independent variables on mini-slump test, plate cohesion meter, induced bleeding test, J-fiber penetration test and compressive strength at 7 and 28 days. The independent variables investigated were the proportions of limestone powder (LSP) and sand, the dosages of superplasticiser (SP) and viscosity agent (VA), and water-to-binder ratio (w/b). A two-level fractional factorial statistical method was used to model the influence of key parameters on properties affecting the behaviour of fresh cement slurry and compressive strength. The models are valid for mixes with 10 to 50% LSP as replacement of cement, 0.02 to 0.06% VA by mass of cement, 0.6 to 1.2% SP and 50 to 150% sand (% mass of binder) and 0.42 to 0.48 w/b. The influences of LSP, SP, VA, sand and W/B were characterised and analysed using polynomial regression which identifies the primary factors and their interactions on the measured properties. Mathematical polynomials were developed for mini-slump, plate cohesion meter, J-fiber penetration test, induced bleeding and compressive strength as functions of LSP, SP, VA, sand and w/b. The estimated results of mini-slump, induced bleeding test and compressive strength from the derived models are compared with results obtained from previously proposed models that were developed for cement paste. The proposed response models of the self-consolidating SIFCON offer useful information regarding the mix optimization to secure a highly penetration of slurry with low compressive strength

Experimental Design to Optimize High-Volume Ash Grout in the Presence of Welan Gum and Superplasticizer

Applications such as soil, rock and oil-well grouting all require enormous amounts of cement and are good examples of areas where a high volume of fly ash could partially replace cement to produce low-cost, environmentally safe and durable concrete. There is an increasing need to identify the rheological properties of cement grout using a simple test to determine the fluidity, and other properties of underwater grouts such as washout resistance and compressive strength. This paper presents statistical models developed using a fractorial design which was carried out to model the influence of key parameters on properties affecting the performance of underwater grout. Such responses of fluidity included mini-slump and flow time measured by Marsh cone, washout resistance, unit weight and compressive strength. The models are valid for mixes with 0.40 to 0.60 water-to-cementitious materials ratio, 0.02 to 0.08% of anti-washout admixture, by mass of binder, and 0.6 to 1.8% of superplasticizer, by mass of cementitious materials. The grout was made with 50% of pulverized-fuel ash replacement, by mass ofcementitious materials. Also presented are the derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of underwater cement grout. Such parameters can be useful to reduce the test protocol needed for proportioning of underwater cement grout. This paper highlighted the influence of W/CM and dosage of antiwashout admixture and superplasticizer on fluidity, washout resistance and compressive strength and attempted also to demonstrate the usefulness of the models to improve understanding of trade-offs between parameters.

Factorial Design of Modelling Mix Proportion Parameters of Underwater Composite Cement Grouts

There is an increasing need to identify the rheological properties of cement grout using a simple test to determine the fluidity, and other properties of underwater applications such as washout resistance and compressive strength. This paper reviews statistical models developed using a factorial design that was carried out to model the influence of key parameters on properties affecting the performance of underwater cement grout. Such responses of fluidity included minislump and flow time measured by Marsh cone, washout resistance, unit weight, and compressive strength. The models are valid for mixes with 0.35–0.55 water-to-binder ratio (W/B), 0.053–0.141% of antiwashout admixture (AWA), by mass of water, and 0.4–1.8% (dry extract) of superplasticizer (SP), by mass of binder. Two types of underwater grout were tested: the first one made with cement and the second one made with 20% of pulverised fuel ash (PFA) replacement, by mass of binder. Also presented are the derived models that enable the identification of underlying primary factors and their interactions that influence the modelled responses of underwater cement grout. Such parameters can be useful to reduce the test protocol needed for proportioning of underwater cement grout. This paper attempts also to demonstrate the usefulness of the models to better understand trade-offs between parameters and compare the responses obtained from the various test methods that are highlighted.

Contribution of process variables to the entrapment efficiency of propranolol hydrochloride within ethylcellulose microspheres prepared by the solvent evaporation method as evaluated using a factorial design

The effects of the process variables, pH of aqueous phase, rate of addition of organic, polymeric, drug-containing phase to aqueous phase, organic:aqueous phase volume ratio and aqueous phase temperature on the entrapment of propranolol hydrochloride in ethylcellulose (N4) microspheres prepared by the solvent evaporation method were examined using a factorial design. The observed range of drug entrapment was 1.43 +/- 0.02%w/w (pH 6, 25 degrees C, phase volume ratio 1:10, fast rate of addition) to 16.63 +/- 0.92%w/w (pH 9, 33 degrees C, phase volume ratio 1:10, slow rate of addition) which corresponded to mean entrapment efficiencies of 2.86 and 33.26, respectively. Increased pH, increased temperature and decreased rate of addition significantly enhanced entrapment efficiency. However, organic:aqueous phase volume ratio did not significantly affect drug entrapment. Statistical interactions were observed between pH and rate of addition, pH and temperature, and temperature and rate of addition. The observed interactions involving pH are suggested to be due to the abilities of increased temperature and slow rate of addition to sufficiently enhance the solubility of dichloromethane in the aqueous phase, which at pH 9, but not pH 6, allows partial polymer precipitation prior to drug partitioning into the aqueous phase. The interaction between temperature and rate of addition is due to the relative lack of effect of increased temperature on drug entrapment following slow rate of addition of the organic phase. In comparison to the effects of pH on drug entrapment, the contributions of the other physical factors examined were limited.

Allometric analysis of Sitka spruce branches:Mechanical versus hydraulic design principles

The geometry of tree branches can have considerable effect on their efficiency in terms of carbon export per unit carbon investment in structure. The purpose of this study was to evaluate different design criteria using data describing the form of Picea sitchensis branches. Allometric analysis of the data suggests that resources are distributed to favour shoots with the greatest opportunity for extension into new space, with priority to the extension of the leader. The distribution of allometric relations of links (branch elements) was tested against two models: the pipe model, based on hydraulic transport requirements, and a static load model based on the requirement of shoots to provide mechanical resistance to static loads. Static load resistance required the load parameter to be proportional to the link radius raised to the power of 4. This was shown to be true within a 95% statistical confidence limit. The pipe model would require total distal length to be proportional to link radius squared but the measured branches did not conform well to this model. The comparison suggests that the diameters of branch elements were more related to the requirements for mechanical load. The cost of following a hydraulic design principle (the pipe model) in terms of mechanical efficiency was estimated and suggested that the pipe model branch would not be mechanically compromised but would use structural resources inefficiently. Resource allocation among branch elements was found to be consistent with mechanical stability criteria but also indicated the possibility of allocation based on other criteria, such as potential light interception by shoots. The evidence suggests that whilst branch topology increments by reiteration of units of morphogenesis, the geometry follows a functional design pattern.

Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I) observational gene expression data: normal environmental condition, (II) interventional gene expression data: growth in rich media, (III) interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

Lovastatin biosynthesis depends on the carbon-nitrogen proportion: model development and controller design

Lovastatin biosynthesis depends on the relative concentrations of dissolved oxygen and the carbon and nitrogen resources. An elucidation of the underlying relationship would facilitate the derivation of a controller for the improvement of lovastatin yield in bioprocesses. To achieve this goal, batch submerged cultivation experiments of lovastatin production by Aspergillus flavipus BICC 5174, using both lactose and glucose as carbon sources, were performed in a 7 liter bioreactor and the data used to determine how the relative concentrations of lactose, glucose, glutamine and oxygen affected lovastatin yield. A model was developed based on these results and its prediction was validated using an independent set of batch data obtained from a 15-liter bioreactor using five statistical measures, including the Willmott index of agreement. A nonlinear controller was designed considering that dissolved oxygen and lactose concentrations could be measured online, and using the lactose feed rate and airflow rate as process inputs. Simulation experiments were performed to demonstrate that a practical implementation of the nonlinear controller would result in satisfactory outcomes. This is the first model that correlates lovastatin biosynthesis to carbon-nitrogen proportion and possesses a structure suitable for implementing a strategy for controlling lovastatin production.

The statistical significance of randomized controlled trial results is frequently fragile: A case for a Fragility Index

Objectives

A P-value <0.05 is one metric used to evaluate the results of a randomized controlled trial (RCT). We wondered how often statistically significant results in RCTs may be lost with small changes in the numbers of outcomes.

Study Design and Setting

A review of RCTs in high-impact medical journals that reported a statistically significant result for at least one dichotomous or time-to-event outcome in the abstract. In the group with the smallest number of events, we changed the status of patients without an event to an event until the P-value exceeded 0.05. We labeled this number the Fragility Index; smaller numbers indicated a more fragile result.

Results

The 399 eligible trials had a median sample size of 682 patients (range: 15-112,604) and a median of 112 events (range: 8-5,142); 53% reported a P-value <0.01. The median Fragility Index was 8 (range: 0-109); 25% had a Fragility Index of 3 or less. In 53% of trials, the Fragility Index was less than the number of patients lost to follow-up.

Conclusion

The statistically significant results of many RCTs hinge on small numbers of events. The Fragility Index complements the P-value and helps identify less robust results.