Estimating process capability index Cpm using a bootstrap sequential sampling procedure

Construction of a confidence interval for process capability index CPM is often based on a normal approximation with fixed sample size. In this article, we describe a different approach in constructing a fixed-width confidence interval for process capability index CPM with a preassigned accuracy by using a combination of bootstrap and sequential sampling schemes. The optimal sample size required to achieve a preassigned confidence level is obtained using both two-stage and modified two-stage sequential procedures. The procedure developed is also validated using an extensive simulation study.

Association between hyperglycaemia and fracture risk in non-diabetic middle-aged and older Australians : a national, population-based prospective study (AusDiab)

Summary : The association between pre-diabetes and fracture risk remains unclear. In this large cohort of middle-aged and older Australian men and women without diabetes, elevated 2-h plasma glucose and pre-diabetes were associated with a reduced 5-year risk of low trauma and all fractures in women, independently of BMI, fasting insulin and other lifestyle factors.

Introduction : We aimed to (1) examine associations between fasting and 2-h plasma glucose (FPG and 2-h PG), fasting insulin and risk of low trauma and all fractures in non-diabetic adults and (2) compare fracture risk between adults with pre-diabetes (impaired glucose tolerance or impaired fasting glucose) and those with normal glucose tolerance (NGT).

Methods : Six thousand two hundred fifty-five non-diabetic men and women aged ≥40 years with NGT (n = 4,855) and pre-diabetes (n = 1,400) were followed for 5 years in the AusDiab Study. Fractures were self-reported.

Results : Five hundred thirty-nine participants suffered at least one fracture (368 women, 171 men), of which the majority (318) occurred after a low-energy trauma (258 women, 60 men). In women, a 2-h PG ≥7.2 mmol/L (highest quartile) was associated with a decreased risk of low trauma and all fractures independent of age and BMI [OR (95% CI) for low trauma fractures, 0.59 (0.40–0.88)], but also fasting insulin, smoking, physical activity, history of fracture, dietary calcium and alcohol intake or menopausal status. There was no effect of 2-h PG on fracture risk in men [OR (95% CI), 1.39 (0.60–3.26)] or any relationship between fracture risk and quartiles of FPG or insulin in either sex. Compared to women with NGT, those with pre-diabetes had a reduced risk of fracture [OR (95% CI) for all fractures, 0.70 (0.52–0.95); for low trauma fractures, 0.75 (0.53–1.05)].

Conclusion : Elevated 2-h PG levels and pre-diabetes were inversely associated with low trauma and/or all fractures in non-diabetic women, independent of BMI and fasting insulin levels.

A model of cause-related marketing for profit-driven and non-profit organizations

Purpose – The purpose of this paper is to describe a model of cause-related marketing (CRM) for both profit-driven (PD) and non-profit (NP) organizations.
Design/methodology/approach – The model consists of two parallel internal and external organizational processes – one representing the process of a NP organization and the other a PD organization. They are interlinked as the outcome of a CRM-partnership is dependent upon their mutual efforts.
Findings – The authors argue that it is essential to remember that a CRM-partnership is a challenge and risk for both the PD and NP organizations that may harm their reputation and position in the marketplace and/or society. CRM has benefits as well as downsides that should not be underestimated nor neglected.
Research limitations/implications – Will the involvement of the PD or NP organizations in the resultant partnership be perceived as commercialism, altruism or a combination of both, in the marketplace and society? A focus on both processes opens up opportunities for further research.
Practical implications – A contribution is that the CRM-model may be used as a guide for both PD and NP organizations in order to reveal whether a CRM-partnership is appropriate for them with a potential partner or not. It may also indicate whether the motives are based upon commercial reasons or altruistic reasons or a combination of both.
Originality/value – The model enables these organizations to think through the process prior to engaging in CRM.

Quantifying urbanisation as a risk factor for non-communicable disease

Aim of this study was to investigate the poorly understood relationship between the process of urbanization and non-communicable diseases (NCDs) in Sri Lanka using a multi-component, quantitative measure of urbanicity.

NCD prevalence data were taken from the Sri Lankan Diabetes and Cardiovascular Study comprising a representative sample of people from seven of the nine provinces in Sri Lanka (n=4,485/5,000; response rate=89.7%). We constructed a measure of the urban environment for seven areas using a seven-item scale based on data from study clusters to develop an ―urbanicity” scale. The items were population size, population density, and access to markets, transportation, communications/media, economic factors, environment/sanitation, health, education, and housing quality. Linear and logistic regression models were constructed to examine the relationship between urbanicity and chronic disease risk factors.

Among men, urbanicity was positively associated with physical inactivity (OR: 3.22; 2.27 – 4.57), high body mass index (OR: 2.45; 95% CI: 1.88 – 3.20) and diabetes mellitus (OR: 2.44; 95% CI: 1.66 – 3.57). Among women, too, urbanicity was positively associated with physical inactivity (OR: 2.29; 95% CI: 1.64 – 3.21), high body mass index (OR: 2.92;95% CI: 2.41 – 3.55) and diabetes mellitus (OR: 2.10; 95% CI: 1.58 – 2.80).

There is a clear relationship between urbanicity and common modifiable risk factors for chronic disease in a representative sample of Sri Lankan adults.

Substrate-induced coagulation (SIC) of nano-disperse carbon black in non-aqueous media : a method of manufacturing highly conductive cathode materials for Li-ion batteries by self-assembly

Substrate-induced coagulation (SIC) is a coating process based on self-assembly for coating different surfaces with fine particulate materials. The particles are dispersed in a suitable solvent and the stability of the dispersion is adjusted by additives. When a surface, pre-treated with a flocculant e.g. a polyelectrolyte, is dipped into the dispersion, it induces coagulation resulting in the deposition of the particles on the surface. A non-aqueous SIC process for carbon coating is presented, which can be performed in polar, aprotic solvents such as N-Methyl-2- pyrrolidinone (NMP). Polyvinylalcohol (PVA) is used to condition the surface of substrates such as mica, copperfoil, silicon-wafers and lithiumcobalt oxide powder, a cathode material used for Li-ion batteries. The subsequent SIC carbon coating produces uniform layers on the substrates and causes the conductivity of lithiumcobalt oxide to increase drastically, while retaining a high percentage of active battery material.

Fast mining of non-derivable episode rules in complex sequences

Researchers have been endeavoring to discover concise sets of episode rules instead of complete sets in sequences. Existing approaches, however, are not able to process complex sequences and can not guarantee the accuracy of resulting sets due to the violation of anti-monotonicity of the frequency metric. In some real applications, episode rules need to be extracted from complex sequences in which multiple items may appear in a time slot. This paper investigates the discovery of concise episode rules in complex sequences. We define a concise representation called non-derivable episode rules and formularize the mining problem. Adopting a novel anti-monotonic frequency metric, we then develop a fast approach to discover non-derivable episode rules in complex sequences. Experimental results demonstrate that the utility of the proposed approach substantially reduces the number of rules and achieves fast processing.

Shear-enhanced solution precipitation : a simple process to produce short polymeric nanofibers

The growing interest in polymeric nanofibers has been increasing the push for the development of simple and efficient nanofiber-preparation techniques. We herein describe how a conventional solution process is readapted to suit the needs for fast and efficient production of short polymeric nanofibers. Poly(ethylene-co-acrylic acid) (PEAA), a semi-crystalline polymer, was used as model. When a PEAA solution was injected into an alcoholic non-solvent while simultaneously applying high shear to the non-solvent system, PEAA nanofibers were obtained with average diameter as thin as 113 nm and length as short as 4.5 _m. The fiber diameter and length were also adjustable by varying the operating parameters. This one-step technique advances the currently available nanofabrication tools by adjusting a widely accepted concept to the nano-scale. It may constitute a viable method for large-scale production of short polymeric nanofibers.

Cancer targeted nanoparticles specifically induce apoptosis in cancer cells and spare normal cells

Curing cancer is the greatest challenge for modern medicine and finding ways to minimize the adverse effects caused by chemotherapeutic agents is of importance in improving patient’s physical conditions. Traditionally, chemotherapy can induce various adverse effects, and these effects are mostly caused by the non-target specific properties of the chemotherapeutic compounds. Recently, the use of nanoparticles has been found to be capable of minimizing these drug-induced adverse effects in animals and in patients during cancer treatment. The use of nanoparticles allows various chemotherapeutic drugs to be targeted to cancer cells with lower dosages. In addition to this, the use of nanoparticles also allows various drugs to be administered to the subjects by an oral route. Here, locked nucleic acid (LNA)-modified epithelial cell adhesion molecules (EpCAM), aptamers (RNA nucleotide), and nucleolin (DNA nucleotide) aptamers have been developed and conjugated on anti-cancer drug-loaded nanocarriers for specific delivery to cancer cells and spare normal cells. Significant amounts of the drug loaded nanocarriers (92 ± 6 %) were found to distribute to the cancer cells at the tumour site and more interestingly, normal cells were unaffected in vitro and in vivo. In this review, the benefits of using nanoparticle-coated drugs in various cancer treatments are discussed. Various nanoparticles that have been tried in improving the target specificity and potency of chemotherapeutic compounds are also described.

Microbial lipases : at the interface of aqueous and non-aqueous media: a review

In recent times, biotechnological applications of microbial lipases in synthesis of many organic molecules have rapidly increased in non-aqueous media. Microbial lipases are the working horses' in biocatalysis and have been extensively studied when their exceptionally high stability in non-aqueous media has been discovered. Stability of lipases in organic solvents makes them commercially feasibile in the enzymatic esterification reactions. Their stability is affected by temperature, reaction medium, water concentration and by the biocatalyst's preparation. An optimization process for ester synthesis from pilot scale to industrial scale in the reaction medium is discussed. The water released during the esterification process can be controlled over a wide range and has a profound effect on the activity of the lipases. Approaches to lipase catalysis like protein engineering, directed evolution and metagenome approach were studied. This review reports the recent development in the field of non-aqueous microbial lipase catalysis and factors controlling the esterification/transesterification processes in organic media.

A non-linear programming-based similarity reasoning scheme for modelling of monotonicity-preserving multi-input fuzzy inference systems

In this paper, the zero-order Sugeno Fuzzy Inference System (FIS) that preserves the monotonicity property is studied. The sufficient conditions for the zero-order Sugeno FIS model to satisfy the monotonicity property are exploited as a set of useful governing equations to facilitate the FIS modelling process. The sufficient conditions suggest a fuzzy partition (at the rule antecedent part) and a monotonically-ordered rule base (at the rule consequent part) that can preserve the monotonicity property. The investigation focuses on the use of two Similarity Reasoning (SR)-based methods, i.e., Analogical Reasoning (AR) and Fuzzy Rule Interpolation (FRI), to deduce each conclusion separately. It is shown that AR and FRI may not be a direct solution to modelling of a multi-input FIS model that fulfils the monotonicity property, owing to the difficulty in getting a set of monotonically-ordered conclusions. As such, a Non-Linear Programming (NLP)-based SR scheme for constructing a monotonicity-preserving multi-input FIS model is proposed. In the proposed scheme, AR or FRI is first used to predict the rule conclusion of each observation. Then, a search algorithm is adopted to look for a set of consequents with minimized root means square errors as compared with the predicted conclusions. A constraint imposed by the sufficient conditions is also included in the search process. Applicability of the proposed scheme to undertaking fuzzy Failure Mode and Effect Analysis (FMEA) tasks is demonstrated. The results indicate that the proposed NLP-based SR scheme is useful for preserving the monotonicity property for building a multi-input FIS model with an incomplete rule base.

Studying non-uniform electrodeposition using the wire beam electrode method

Nonuniform electrodeposition is a major concern in almost every practical electrodeposition application. The ablility to control nonuniformity in electrodeposition is the key to successful plating for corrosion resistance, and more especially to meeting the very exacting requirements of electroforming, electrodeposition. This paper presents a novel technique namely the wire beam electrode (WBE) for characterizing and monitoring nonuniform electroplating processes. For the first time, the nonuniform distribution of electroplating currents (NDEC) has been mapped. Preliminary experimental results indicated that electrochemical heterogeneity was the key factor affecting NDEC. The secondary current distribution, rather than the primary current distribution, played a major role in determining the NDEC. This work suggests that the WBE is a practical tool for characterizing and optimizing electrodeposition processes and for verifying the accuracy and completeness of mathematic modelling of electrodeposition processes.

Fuzzy simulation of pedestrian walking path considering local environmental stimuli

Pedestrian steering activity is a perception-based decision making process that involves interaction with the surrounding environment and insight into environmental stimuli. There are many stimuli within the environment that influence pedestrian wayfinding behaviour during walking activities. However, compelling factors such as individual physical and psychological characteristics and trip intention cause the behaviour become a very fuzzy concept. In this paper pedestrian steering behaviour is modelled using a fuzzy logic approach. The objective of this research is to simulate pedestrian walking paths in indoor public environments during normal and non-panic situations. The proposed algorithm introduces a fuzzy logic framework to predict the impact of perceived attractive and repulsive stimuli, within the pedestrian's field of view, on movement direction. Environmental stimuli are quantified using the social force method. The algorithm is implemented in a simulated area of an office corridor consist of a printer and exit door. Stochastic simulation using the proposed fuzzy algorithm generated realistic walking trajectories, contour map of dynamic change of environmental effects in each step of movement and high flow areas in the corridor.

Non-uniform sparsity in rapid compressive sensing MRI

Magnetic Resonance Imaging (MRI) is one of the prominent medical imaging techniques. This process is time-consuming and can take several minutes to acquire one image. The aim of this research is to reduce the imaging process time of MRI. This issue is addressed by reducing the number of acquired measurements using theory of Compressive Sensing (CS). Compressive Sensing exploits sparsity in MR images. Randomly under sampled k-space generates incoherent noise which can be handled using a nonlinear image reconstruction method. In this paper, a new framework is presented based on the idea to exploit non-uniform nature of sparsity in MR images, where local sparsity constrains were used instead of traditional global constraint, to further reduce the sample set. Experimental results and comparison with CS using global constraint are demonstrated.

A slice sampler for restricted hierarchical beta process with applications to shared subspace learning

Hierarchical beta process has found interesting applications in recent years. In this paper we present a modified hierarchical beta process prior with applications to hierarchical modeling of multiple data sources. The novel use of the prior over a hierarchical factor model allows factors to be shared across different sources. We derive a slice sampler for this model, enabling tractable inference even when the likelihood and the prior over parameters are non-conjugate. This allows the application of the model in much wider contexts without restrictions. We present two different data generative models – a linear Gaussian-Gaussian model for real valued data and a linear Poisson-gamma model for count data. Encouraging transfer learning results are shown for two real world applications – text modeling and content based image retrieval.

Knowledge brokering between researchers and policymakers in Fiji to develop policies to reduce obesity: a process evaluation

The importance of using research evidence in decision making at the policy level has been increasingly recognized. However, knowledge brokering to engage researchers and policymakers in government and non-government organizations is challenging. This paper describes and evaluates the knowledge exchange processes employed by the Translational Research on Obesity Prevention in Communities (TROPIC) project that was conducted from July 2009 to April 2012 in Fiji. TROPIC aimed to enhance: the evidence-informed decision making skills of policy developers; and awareness and utilization of local and other obesity-related evidence to develop policies that could potentially improve the nation’s food and physical activity environments. The specific research question was: Can a knowledge brokering approach advance evidence-informed policy development to improve eating and physical activity environments in Fiji.