Vibrational spectroscopic study of the uranyl selenite mineral derriksite Cu4UO2(SeO3)2(OH)6⋅H2O

Raman spectrum of the mineral derriksite Cu4UO2(SeO3)2(OH)6⋅H2O was studied and complemented by the infrared spectrum of this mineral. Both spectra were interpreted and partly compared with the spectra of demesmaekerite, marthozite, larisaite, haynesite and piretite. Observed Raman and infrared bands were attributed to the (UO2)2+, (SeO3)2−, (OH)− and H2O vibrations. The presence of symmetrically distinct hydrogen bonded molecule of water of crystallization and hydrogen bonded symmetrically distinct hydroxyl ions was inferred from the spectra in the derriksite unit cell. Approximate U–O bond lengths in uranyl and O–H⋯O hydrogen bond lengths were calculated from the Raman and infrared spectra of derriksite.

The GSTM1 null genotype confers an increased risk for Solar Keratosis Development in an Australian Caucasian Population

Solar keratoses affect approximately 50% of Australian Caucasians aged over 40 y. Solar keratoses can undergo malignant transformation into squamous cell carcinoma followed by possible metastasis and are risk factors for basal cell carcinoma, melanoma, and squamous cell carcinoma. The glutathione-S-transferase genes play a part in detoxification of carcinogens and mutagens, including some produced by ultraviolet radiation. This study examined the role of glutathione-S-transferase M1, T1, P1, and Z1 gene polymorphisms in susceptibility to solar keratoses development. Using DNA samples from volunteers involved in the Nambour Skin Cancer Prevention Trial, allele and genotype frequencies were determined using polymerase chain reaction and restriction enzyme digestion. No significant differences were detected in glutathione-S-transferase P1 and glutathione-S-transferase Z1 allele or genotype frequencies; however, a significant association between glutathione-S-transferase M1 genotypes and solar keratoses development was detected (p=0.003) with null individuals having an approximate 2-fold increase in risk for solar keratoses development (odds ratio: 2.1; confidence interval: 1.3-3.5) and a significantly higher increase in risk in conjunction with high outdoor exposure (odds ratio: 3.4; confidence interval: 1.9-6.3). Also, a difference in glutathione-S-transferase T1 genotype frequencies was detected (p=0.039), although considering that multiple testing was undertaken, this was found not to be significant. Fair skin and inability to tan were found to be highly significant risk factors for solar keratoses development with odds ratios of 18.5 (confidence interval: 5.7-59.9) and 7.4 (confidence interval: 2.6-21.0), respectively. Overall, glutathione-S-transferase M1 conferred a significant increase in risk of solar keratoses development, particularly in the presence of high outdoor exposure and synergistically with known phenotypic risk factors of fair skin and inability to tan.

Patellar tendon ultrasonography in asymptomatic active athletes reveals hypoechoic regions : a study of 320 tendons

OBJECTIVE: To compare patellar tendon sonographic findings in active, currently asymptomatic, elite athletes with those in nonathletic controls. DESIGN: Cross-sectional cohort study with convenience control sample. SETTING: The Victorian Institute of Sport Tendon Study Group, an institutional elite athlete study group in Australia. PATIENTS AND PARTICIPANTS: Two hundred elite male and female athletes from the sports of basketball, cricket, netball, and Australian rules football. Forty athletes who had current symptoms of jumper's knee were excluded from analysis, leaving 320 subject tendons in athletes who were currently asymptomatic. Twenty-seven nonathletic individuals served as controls. MAIN OUTCOME MEASURE: Sonographic patellar tendon appearance. We measured the dimensions of subject tendons and noted the presence or absence of hypoechoic regions and tendon calcification. Dimensions of hypoechoic regions were measured, and approximate cross-sectional areas were calculated. Chi-squared analysis was used to test the prevalence of hypoechoic regions in subjects and controls and men and women. RESULTS: In currently asymptomatic subjects, hypoechoic regions were more prevalent in athlete tendons (22%) than in controls (4%), in male subject tendons (30%) than in female subjects (14%), and in basketball players (32%) than in other athletes (9%) (all p < 0.01). Bilateral tendon abnormalities were equally prevalent in men and women but more prevalent in basketball players (15%) than in other athletes (3%) (p < 0.05). Sonographic hypoechoic regions were present in 35 of 250 (14%) patellar tendons in athletes who had never had anterior knee pain. CONCLUSIONS: Patellar tendon sonographic hypoechoic areas were present in asymptomatic patellar tendons of a proportion of elite athletes but rarely present in controls. This has implications for clinicians managing athletes with anterior knee pain.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Vision-based estimation of airborne target pseudobearing rate using hidden Markov model filters

The problem of estimating pseudobearing rate information of an airborne target based on measurements from a vision sensor is considered. Novel image speed and heading angle estimators are presented that exploit image morphology, hidden Markov model (HMM) filtering, and relative entropy rate (RER) concepts to allow pseudobearing rate information to be determined before (or whilst) the target track is being estimated from vision information.

Bayesian indirect inference using a parametric auxiliary model

Indirect inference (II) is a methodology for estimating the parameters of an intractable (generative) model on the basis of an alternative parametric (auxiliary) model that is both analytically and computationally easier to deal with. Such an approach has been well explored in the classical literature but has received substantially less attention in the Bayesian paradigm. The purpose of this paper is to compare and contrast a collection of what we call parametric Bayesian indirect inference (pBII) methods. One class of pBII methods uses approximate Bayesian computation (referred to here as ABC II) where the summary statistic is formed on the basis of the auxiliary model, using ideas from II. Another approach proposed in the literature, referred to here as parametric Bayesian indirect likelihood (pBIL), we show to be a fundamentally different approach to ABC II. We devise new theoretical results for pBIL to give extra insights into its behaviour and also its differences with ABC II. Furthermore, we examine in more detail the assumptions required to use each pBII method. The results, insights and comparisons developed in this paper are illustrated on simple examples and two other substantive applications. The first of the substantive examples involves performing inference for complex quantile distributions based on simulated data while the second is for estimating the parameters of a trivariate stochastic process describing the evolution of macroparasites within a host based on real data. We create a novel framework called Bayesian indirect likelihood (BIL) which encompasses pBII as well as general ABC methods so that the connections between the methods can be established.

Fully Bayesian experimental design for pharmacokinetic studies

Utility functions in Bayesian experimental design are usually based on the posterior distribution. When the posterior is found by simulation, it must be sampled from for each future data set drawn from the prior predictive distribution. Many thousands of posterior distributions are often required. A popular technique in the Bayesian experimental design literature to rapidly obtain samples from the posterior is importance sampling, using the prior as the importance distribution. However, importance sampling will tend to break down if there is a reasonable number of experimental observations and/or the model parameter is high dimensional. In this paper we explore the use of Laplace approximations in the design setting to overcome this drawback. Furthermore, we consider using the Laplace approximation to form the importance distribution to obtain a more efficient importance distribution than the prior. The methodology is motivated by a pharmacokinetic study which investigates the effect of extracorporeal membrane oxygenation on the pharmacokinetics of antibiotics in sheep. The design problem is to find 10 near optimal plasma sampling times which produce precise estimates of pharmacokinetic model parameters/measures of interest. We consider several different utility functions of interest in these studies, which involve the posterior distribution of parameter functions.

Evolving progress in oncologic and operative outcomes for esophageal and junctional cancer : lessons from the experience of a high-volume center

Objective: Modern series from high-volume esophageal centers report an approximate 40% 5-year survival in patients treated with curative intent and postoperative mortality rates of less than 4%. An objective analysis of factors that underpin current benchmarks within high-volume centers has not been performed. Methods: Three time periods were studied, 1990 to 1998 (period 1), 1999 to 2003 (period 2), and 2004 to 2008 (period 3), in which 471, 254, and 342 patients, respectively, with esophageal cancer were treated with curative intent. All data were prospectively recorded, and staging, pathology, treatment, operative, and oncologic outcomes were compared. Results: Five-year disease-specific survival was 28%, 35%, and 44%, and in-hospital postoperative mortality was 6.7%, 4.4%, and 1.7% for periods 1 to 3, respectively (P < .001). Period 3, compared with periods 1 and 2, respectively, was associated with significantly (P < .001) more early tumors (17% vs 4% and 6%), higher nodal yields (median 22 vs 11 and 18), and a higher R0 rate in surgically treated patients (81% vs 73% and 75%). The use of multimodal therapy increased (P < .05) across time periods. By multivariate analysis, age, T stage, N stage, vascular invasion, R status, and time period were significantly (P < .0001) associated with outcome. Conclusions: Improved survival with localized esophageal cancer in the modern era may reflect an increase of early tumors and optimized staging. Important surgical and pathologic standards, including a higher R0 resection rate and nodal yields, and lower postoperative mortality, were also observed. Copyright © 2012 by The American Association for Thoracic Surgery.

A conceptualization of complexity in IS-driven organizational transformations

Organizational transformations reliant on successful ICT system developments (continue to) fail to deliver projected benefits even when contemporary governance models are applied rigorously. Modifications to traditional program, project and systems development management methods have produced little material improvement to successful transformation as they are unable to routinely address the complexity and uncertainty of dynamic alignment of IS investments and innovation. Complexity theory provides insight into why this phenomenon occurs and is used to develop a conceptualization of complexity in IS-driven organizational transformations. This research-in-progress aims to identify complexity formulations relevant to organizational transformation. Political/power based influences, interrelated business rules, socio-technical innovation, impacts on stakeholders and emergent behaviors are commonly considered as characterizing complexity while the proposed conceptualization accommodates these as connectivity, irreducibility, entropy and/or information gain in hierarchically approximation and scaling, number of states in a finite automata and/or dimension of attractor, and information and/or variety.

Development of a new signal processing diagnostic tool for vibration signals acquired in transient conditions

The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

Effectiveness of MED for Fault Diagnosis in Roller Bearings

Diagnostics of rolling element bearings is usually performed by means of vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. The aim is to monitor the integrity of the bearing components, in order to avoid catastrophic failures, or to implement condition based maintenance strategies. In particular, the trend in this field is to combine in a single algorithm different signal-enhancement and signal-analysis techniques. Among the first ones, Minimum Entropy Deconvolution (MED) has been pointed out as a key tool able to highlight the effect of a possible damage in one of the bearing components within the vibration signal. This paper presents the application of this technique to signals collected on a simple test-rig, able to test damaged industrial roller bearings in different working conditions. The effectiveness of the technique has been tested, comparing the results of one undamaged bearing with three bearings artificially damaged in different locations, namely on the inner race, outer race and rollers. Since MED performances are dependent on the filter length, the most suitable value of this parameter is defined on the basis of both the application and measured signals. This represents an original contribution of the paper.

Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED

The signal processing techniques developed for the diagnostics of mechanical components operating in stationary conditions are often not applicable or are affected by a loss of effectiveness when applied to signals measured in transient conditions. In this chapter, an original signal processing tool is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition, Minimum Entropy Deconvolution and the analytical approach of the Hilbert transform. The tool has been developed to detect localized faults on bearings of traction systems of high speed trains and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on envelope analysis or spectral kurtosis, which represent until now the landmark for bearings diagnostics.

Advantages of exploiting projection structure for segmenting dense 3D point clouds

Timely and comprehensive scene segmentation is often a critical step for many high level mobile robotic tasks. This paper examines a projected area based neighbourhood lookup approach with the motivation towards faster unsupervised segmentation of dense 3D point clouds. The proposed algorithm exploits the projection geometry of a depth camera to find nearest neighbours which is time independent of the input data size. Points near depth discontinuations are also detected to reinforce object boundaries in the clustering process. The search method presented is evaluated using both indoor and outdoor dense depth images and demonstrates significant improvements in speed and precision compared to the commonly used Fast library for approximate nearest neighbour (FLANN) [Muja and Lowe, 2009].

Metabolomic analysis of siderophore cheater mutants reveals metabolic costs of expression in uropathogenic escherichia coli

Bacterial siderophores are a group of chemically diverse, virulence-associated secondary metabolites whose expression exerts metabolic costs. A combined bacterial genetic and metabolomic approach revealed differential metabolomic impacts associated with biosynthesis of different siderophore structural families. Despite myriad genetic differences, the metabolome of a cheater mutant lacking a single set of siderophore biosynthetic genes more closely approximate that of a nonpathogenic K12 strain than its isogenic, uropathogen parent strain. Siderophore types associated with greater metabolomic perturbations are less common among human isolates, suggesting that metabolic costs influence success in a human population. Although different siderophores share a common iron acquisition function, our analysis shows how a metabolomic approach can distinguish their relative metabolic impacts in E.coli.

Comparing methods for modelling spreading cell fronts

Spreading cell fronts play an essential role in many physiological processes. Classically, models of this process are based on the Fisher-Kolmogorov equation; however, such continuum representations are not always suitable as they do not explicitly represent behaviour at the level of individual cells. Additionally, many models examine only the large time asymptotic behaviour, where a travelling wave front with a constant speed has been established. Many experiments, such as a scratch assay, never display this asymptotic behaviour, and in these cases the transient behaviour must be taken into account. We examine the transient and asymptotic behaviour of moving cell fronts using techniques that go beyond the continuum approximation via a volume-excluding birth-migration process on a regular one-dimensional lattice. We approximate the averaged discrete results using three methods: (i) mean-field, (ii) pair-wise, and (iii) one-hole approximations. We discuss the performace of these methods, in comparison to the averaged discrete results, for a range of parameter space, examining both the transient and asymptotic behaviours. The one-hole approximation, based on techniques from statistical physics, is not capable of predicting transient behaviour but provides excellent agreement with the asymptotic behaviour of the averaged discrete results, provided that cells are proliferating fast enough relative to their rate of migration. The mean-field and pair-wise approximations give indistinguishable asymptotic results, which agree with the averaged discrete results when cells are migrating much more rapidly than they are proliferating. The pair-wise approximation performs better in the transient region than does the mean-field, despite having the same asymptotic behaviour. Our results show that each approximation only works in specific situations, thus we must be careful to use a suitable approximation for a given system, otherwise inaccurate predictions could be made.