<i>miniPixD</i>: a compact sample analysis system which combines X-ray imaging and diffraction

This paper introduces miniPixD: a new, compact system that utilises transmission X-ray imaging and X-ray diffraction (XRD) to locate and identify materials of interest within an otherwise opaque volume. The system and the embodied techniques have utility in security screening, medical diagnostics, non-destructive testing (NDT) and quality assurance (QA). This paper outlines the design of the system including discussion on the choice of components and presents some data from relevant samples which are compared to other energy dispersive and angular dispersive XRD techniques

Determination of ingredients in packaged pharmaceutical tablets by energy dispersive X‐ray diffraction and maximum likelihood principal component analysis multivariate curve resolution‐alternating least squares with correlation constraint

Energy dispersive X‐ray diffraction (EDXRD) and maximum likelihood principal component analysis multivariate curve resolution‐alternating least squares (MLPCA‐MCR‐ALS) with correlation constraint were used to quantify the composition of packaged pharmaceutical formulations. Recorded EDXRD profiles from unpackaged and packaged samples of ternary mixtures were modelled together in order to recover the concentrations as well as the pure profiles of the constituent compounds. MLPCA was used as a data pretreatment step to MCR‐ALS, accounting for the high noise and nonconstant variance observed in the EDXRD profiles and was shown to improve the resolution accuracy of MCR‐ALS for the data set. Local correlation constraints were applied in the MCR‐ALS procedure in order to model unpackaged and packaged samples simultaneously while accounting for the matrix effect of the packaging materials. The composition of the formulations was estimated with root‐mean‐square error of prediction for each component, including paracetamol, being approximately 2.5 %w/w for unpackaged and packaged samples. Paracetamol concentration was resolved simultaneously for the unpackaged and packaged samples to a greater degree of accuracy than achieved by partial least squares regression (PLSR) when modelling the contexts separately. By modelling the effects of the packaging and incorporating accurate reference information of unpackaged samples into the resolution of packaged samples, the potential of EDXRD and MLPCA‐MCR‐ALS for the identification and quantification of packaged solid‐dosage medicine in nondestructive screening and counterfeit medicine detection has been raised

Multivariate calibration of energy-dispersive X-ray diffraction data for predicting the composition of pharmaceutical tablets in packaging

A system using energy-dispersive X-ray diffraction (EDXRD) has been developed and tested using multivariate calibration for the quantitative analysis of tablet-form mixtures of common pharmaceutical ingredients. A principal advantage of EDXRD over the more traditional and common angular dispersive X-ray diffraction technique (ADXRD) is the potential of EDXRD to analyse tablets within their packaging, due to the higher energy X-rays used. In the experiment, a series of caffeine, paracetamol and microcrystalline cellulose mixtures were prepared and pressed into tablets. EDXRD profiles were recorded on each sample and a principal component analysis (PCA) was carried out in both unpackaged and packaged scenarios. In both cases the first two principal components explained >98% of the between-sample variance. The PCA projected the sample profiles into two dimensional principal component space in close accordance to their ternary mixture design, demonstrating the discriminating potential of the EDXRD system. A partial least squares regression (PLSR) model was built with the samples and was validated using leave-one-out cross-validation. Low prediction errors of between 2% and 4% for both unpackaged and packaged tablets were obtained for all three chemical compounds. The prediction capability through packaging demonstrates a truly non-destructive method for quantifying tablet composition and demonstrates good potential for EDXRD to be applied in the field of counterfeit medicine screening and pharmaceutical quality control

An integarted surgical suite management information system

The operational aspects, application areas, and results achieved from an integrated surgical suite management information system are described. The system, which has been operating within Henry Ford Hospital in Detroit, Michigan, for 4 years, captures comprehensive data for each surgical episode, performs extensive edits on these data to assure data base integrity, and utilizes this data base in multiple applications. These applications include fixed-format reporting for medical staff and management; ad hoc retrieval capabilities to support research, education, and decision making; and linkage to other hospital systems to reduce both data redundancy and paper flow.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45000/1/10916_2005_Article_BF02222176.pd

The effects of amisulpride on five dimensions of psychopathology in patients with schizophrenia: a prospective open- label study

BACKGROUND: The efficacy of antipsychotics can be evaluated using the dimensional models of schizophrenic symptoms. The D(2)/D(3)-selective antagonist amisulpride has shown similar efficacy and tolerability to other atypical antipsychotics. The aim of the present study was to determine the efficacy of amisulpride on the dimensional model of schizophrenic symptoms and tolerability in latin schizophrenic patients. METHOD: Eighty schizophrenic patients were enrolled and 70 completed a prospective open-label 3-month study with amisulpride. The schizophrenic symptoms, psychosocial functioning and side-effects were evaluated with standardized scales. RESULTS: The patients showed significant improvement in the five dimensions evaluated. Amisulpride (median final dose 357.1 mg/d) was well-tolerated without treatment-emergent extrapyramidal side-effects. CONCLUSION: Amisulpride showed efficacy on different psychopathological dimensions and was well tolerated, leading to consider this drug a first line choice for the treatment of schizophrenia

Demonstration of surface electron rejection with interleaved germanium detectors for dark matter searches

The following article appeared in Applied Physics Letters 103.16 (2013): 164105 and may be found at http://scitation.aip.org/content/aip/journal/apl/100/26/10.1063/1.4729825The SuperCDMS experiment in the Soudan Underground Laboratory searches for dark matter with a 9-kg array of cryogenic germanium detectors. Symmetric sensors on opposite sides measure both charge and phonons from each particle interaction, providing excellent discrimination between electron and nuclear recoils, and between surface and interior events. Surface event rejection capabilities were tested with two 210 Pb sources producing ∼130 beta decays/hr. In ∼800 live hours, no events leaked into the 8–115 keV signal region, giving upper limit leakage fraction 1.7 × 10−5 at 90% C.L., corresponding to < 0.6 surface event background in the future 200-kg SuperCDMS SNOLAB experiment.This work is supported in part by the National Science Foundation (Grant Nos. AST-9978911, NSF-0847342, PHY-1102795,NSF-1151869, PHY-0542066, PHY-0503729, PHY-0503629, PHY-0503641, PHY-0504224, PHY-0705052,PHY-0801708, PHY-0801712, PHY-0802575, PHY-0847342, PHY-0855299, PHY-0855525, and PHY-1205898), by the Department of Energy (Contract Nos. DE-AC03-76SF00098, DE-FG02-92ER40701, DE-FG02-94ER40823,DE-FG03-90ER40569, DE-FG03-91ER40618, and DESC0004022),by NSERC Canada (Grant Nos. SAPIN 341314 and SAPPJ 386399), and by MULTIDARK CSD2009-00064 and FPA2012-34694. Fermilab is operated by Fermi Research Alliance, LLC under Contract No. De-AC02-07CH11359, while SLAC is operated under Contract No. DE-AC02-76SF00515 with the United States Department of Energy

A Multi-Element Detector System for Intelligent Imaging: I-ImaS

I-ImaS is a European project aiming to produce new, intelligent x-ray imaging systems using novel APS sensors to create optimal diagnostic images. Initial systems concentrate on mammography and encephalography. Later development will yield systems for other types of radiography such as industrial QA and homeland security. The I-ImaS system intelligence, due to APS technology and FPGAs, allows real-time analysis of data during image acquisition, giving the capability to build a truly adaptive imaging system with the potential to create images with maximum diagnostic information within given dose constraints. A companion paper deals with the DAQ system and preliminary characterization. This paper considers the laboratory x-ray characterization of the detector elements of the I-ImaS system. The characterization of the sensors when tiled to form a strip detector will be discussed, along with the appropriate correction techniques formulated to take into account the misalignments between individual sensors within the array. Preliminary results show that the detectors have sufficient performance to be used successfully in the initial mammographic and encephalographic I-ImaS systems under construction and this paper will further discuss the testing of these systems and the iterative processes used for intelligence upgrade in order to obtain the optimal algorithms and setting

Quantitative energy-dispersive x-ray diffraction for identification of counterfeit medicines: a preliminary study

The prevalence of counterfeit and substandard medicines has been growing rapidly over the past decade, and fast, nondestructive techniques for their detection are urgently needed to counter this trend. In this study, energy-dispersive X-ray diffraction (EDXRD) combined with chemometrics was assessed for its effectiveness in quantitative analysis of compressed powder mixtures. Although EDXRD produces lower-resolution diffraction patterns than angular-dispersive X-ray diffraction (ADXRD), it is of interest for this application as it carries the advantage of allowing the analysis of tablets within their packaging, due to the higher energy X-rays used. A series of caffeine, paracetamol and microcrystalline cellulose mixtures were prepared with compositions between 0 - 100 weight% in 20 weight% steps (22 samples in total, including a centroid mixture), and were pressed into tablets. EDXRD spectra were collected in triplicate, and a principal component analysis (PCA) separated these into their correct positions in the ternary mixture design. A partial least-squares (PLS) regression model calibrated using this training set was validated using both segmented cross-validation, and with a test set of six samples (mixtures in 8:1:1 and 5⅓:2⅓:2⅓ ratios) – the latter giving a root-mean square error of prediction (RMSEP) of 1.30, 2.25 and 2.03 weight% for caffeine, paracetamol and cellulose respectively. These initial results are promising, with RMSEP values on a par with those reported in the ADXRD literature

X-ray backscatter sensing of defects in carbon fibre composite materials

X-ray backscatter (XBS) provides a novel approach to the field of non-destructive evaluation (NDE) in the aerospace industry. XBS is conducted by collecting the radiation which is scattered from a sample illuminated by a well-defined Xray beam, and the technique enables objects to be scanned at a sub-surface level using single-sided access, and without the requirement for coupling with the sample. Single-sided access is of particular importance when the objects of interest are very large, such as aircraft components. Carbon fibre composite materials are being increasingly used as a structural material in aircraft, and there is an increasing demand for techniques which are sensitive to the delaminations which occur in these composites as a result of both large impacts and barely visible impact damage (BVID). The XBS signal is greatly enhanced for plastics and lightweight materials, making it an ideal candidate for probing sub-surface damage and defects in carbon fibre composites. Here we present both computer modelling and experimental data which demonstrate the capability of the XBS technique for identifying hidden defects in carbon fibre