Gas-phase syntheses of three isomeric C5H2 radical anions and their elusive neutrals. A joint experimental and theoretical study

Three different radical anions of the empirical formula C5H2 have been generated by negative ion chemical ionization mass spectrometry in the gas phase. The isomers C4CH2 •-, and HC5H•- have been synthesized by unequivocal routes and their connectivities confirmed by deuterium labeling, charge reversal, and neutralization reionization experiments. The results also provided evidence for the existence of neutrals C4CH2, C2CHC2H, and HC5H as stable species; this is the first reported observation of C2CHC2H. Ab initio calculations confirm these structures to be minima on the anion and neutral potential energy surfaces.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

Joint 2D and 3D cues for image segmentation towards robotic applications

This thesis investigates the fusion of 3D visual information with 2D image cues to provide 3D semantic maps of large-scale environments in which a robot traverses for robotic applications. A major theme of this thesis was to exploit the availability of 3D information acquired from robot sensors to improve upon 2D object classification alone. The proposed methods have been evaluated on several indoor and outdoor datasets collected from mobile robotic platforms including a quadcopter and ground vehicle covering several kilometres of urban roads.

Generation of three isomers of C7H- in the gas phase. A joint experimental and theoretical study

Three anion isomers of formula C7H have been synthesised in the mass spectrometer by unequivocal routes. The structures of the isomers are \[HCCC(C-2)(2)](-), C6CH- and C2CHC4-. One of these, \[HCCC(C-2)(2)](-), is formed in sufficient yield to allow it to be charge stripped to the corresponding neutral radical.

Mortality following hip arthroplasty—inappropriate use of National Joint Registry (NJR) data

Mortality following hip arthroplasty is affected by a large number of confounding variables each of which must be considered to enable valid interpretation. Relevant variables available from the 2011 NJR data set were included in the Cox model. Mortality rates in hip arthroplasty patients were lower than in the age-matched population across all hip types. Age at surgery, ASA grade, diagnosis, gender, provider type, hip type and lead surgeon grade all had a significant effect on mortality. Schemper's statistic showed that only 18.98% of the variation in mortality was explained by the variables available in the NJR data set. It is inappropriate to use NJR data to study an outcome affected by a multitude of confounding variables when these cannot be adequately accounted for in the available data set.

Management of periprosthetic joint infection after total hip arthroplasty using a Custom Made Articulating Spacer (CUMARS); the exeter experience

Periprosthetic joint infection (PJI) after THA is a major complication with an incidence of 1-3%. We report our experiences with a technique using a custom-made articulating spacer (CUMARS) at the first of two-stage treatment for PJI. This technique uses widely available all-polyethylene acetabular components and the Exeter Universal stem, fixed using antibiotic loaded acrylic cement. Seventy-six hips were treated for PJI using this technique. Performed as the first of a two-stage procedure, good functional results were commonly seen, leading to postponing second stage indefinitely with retention of the CUMARS prosthesis in 34 patients. The CUMARS technique presents an alternative to conventional spacers, using readily available components that are well tolerated, allowing weight bearing and mobility, and achieving comparable eradication rates.

Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm

Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.

Segmental torso masses and joint torques produced by gravity in the adolescent scoliotic spine

Introduction Calculating segmental torso masses in Adolescent Idiopathic Scoliosis (AIS) patients allows the gravitational loading on the scoliotic spine during relaxed standing to be estimated. Methods Low dose CT data was used to calculate vertebral level-by-level torso masses and spinal joint torques for 20 female AIS patients (mean age 15.0 ± 2.7 years, mean Cobb angle 53 ± 7.1°). ImageJ software (v1.45 NIH USA) was used to threshold the T1 to L5 CT images and calculate the segmental torso volume and mass for each vertebral level. Masses for the head, neck and arms were taken from published data. Intervertebral joint torques in the coronal and sagittal planes at each vertebral level were found from the position of the centroid of the segment masses relative to the joint centres (assumed to be at the centre of the intervertebral disc. The joint torque at each level was found by summing torque contributions for all segments above that joint. Results Segmental torso mass increased from 0.6kg at T1 to 1.5kg at L5. The coronal plane joint torques due to gravity were 5-7Nm at the apex of the curve; sagittal torques were 3-5.4Nm. Conclusion CT scans were in the supine position and curve magnitudes are known to be smaller than those in standing. Hence, this study has shown that gravity produces joint torques potentially of higher than 7Nm in the coronal plane and 5Nm in the sagittal plane during relaxed standing in scoliosis patients. The magnitude of these torques may help to explain the mechanics of AIS progression and the mechanics of bracing. This new data on torso segmental mass in AIS patients will assist biomechanical models of scoliosis.

Gravity-induced coronal plane joint moments in the adolescent scoliotic spine

INTRODUCTION Calculating segmental (vertebral level-by-level) torso masses in Adolescent Idiopathic Scoliosis (AIS) patients allows the gravitational loading on the scoliotic spine during relaxed standing to be estimated. METHODS Existing low dose CT scans were used to calculate vertebral level-by-level torso masses and joint moments occurring in the spine for a group of female AIS patients with right-sided thoracic curves. Image processing software, ImageJ (v1.45 NIH USA) was used to reconstruct the torso segments and subsequently measure the torso volume and mass corresponding to each vertebral level. Body segment masses for the head, neck and arms were taken from published anthropometric data. Intervertebral joint moments at each vertebral level were found by summing each of the torso segment masses above the required joint and multiplying it by the perpendicular distance to the centre of the disc. RESULTS AND DISCUSSION Twenty patients were included in this study with a mean age of 15.0±2.7 years and a mean Cobb angle 52±5.9°. The mean total trunk mass, as a percentage of total body mass, was 27.8 (SD 0.5) %. Mean segmental torso mass increased inferiorly from 0.6kg at T1 to 1.5kg at L5. The coronal plane joint moments during relaxed standing were typically 5-7Nm at the apex of the curve (Figure 1), with the highest apex joint of 7Nm. CT scans were performed in the supine position and curve magnitudes are known to be 7-10° smaller than those measured in standing [1]. Therefore joint moments produced by gravity will be greater than those calculated here. CONCLUSIONS Coronal plane joint moments as high as 7Nm can occur during relaxed standing in scoliosis patients, which may help to explain the mechanics of AIS progression. The body mass distributions calculated in this study can be used to estimate joint moments derived using other imaging modalities such as MRI and subsequently determine if a relationship exists between joint moments and progressive vertebral deformity.

Use of the biolistic particle delivery system to transform fungal genomes

Biolistic delivery of transforming DNA into fungal genomes, especially when performed on uninucleate haploid conidia, has proven successful in bypassing the time-consuming repetitive purification of protoplasts used for the widely applied polyethylene glycol-mediated method. Biolistic transformation is also relatively quick compared to other available methods and provides a high percentage of stable transformants.

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.

Information and communication technologies transform the practice of medicine

Information and Communication Technologies are dramatically transforming Allopathic medicine. Technological developments including Tele-medicine, Electronic health records, Standards to ensure computer systems inter-operate, Data mining, Simulation, Decision Support and easy access to medical information each contribute to empowering patients in new ways and change the practice of medicine. To date, informatics has had little impact on Ayurvedic medicine. This tutorial provides an introduction to key informatics initiatives in Allopothic medicine using real examples and suggests how applications can be applied to Ayurvedic medicine.

Identifying weak linear features with the "coalescing shortest path image transform"

The detection of line-like features in images finds many applications in microanalysis. Actin fibers, microtubules, neurites, pilis, DNA, and other biological structures all come up as tenuous curved lines in microscopy images. A reliable tracing method that preserves the integrity and details of these structures is particularly important for quantitative analyses. We have developed a new image transform called the "Coalescing Shortest Path Image Transform" with very encouraging properties. Our scheme efficiently combines information from an extensive collection of shortest paths in the image to delineate even very weak linear features. © Copyright Microscopy Society of America 2011.