Quadrupolar hard Gaussian-overlap fluid

Monte Carlo simulations are performed for a system of hard Gaussianoverlap molecules with embedded permanent quadrupole moment. Two shapes of the hard bodies are considered, with characteristic parameter ~c = 1-792 and 2.2 and three values of the quadrupole moment. The results obtained for the residual internal energy, Helmholtz function and compressibility factor at three densities for g = 1.792 and one density for g = 2-2 are used to test the recently proposed perturbation theory of polar non-spherical-molecule fluids. Introduction Description of the equilibrium behaviour of pure fluids and their mixtures is of great importance both for theoretical and chemical engineering practice. Following progress in the understanding and description of the behaviour of non-polar fluids composed of molecules of spherical or non-spherical shape [1-3] and fluids of spherical molecules with different electrostatic interactions For non-polar fluids convex-molecule perturbation theory has proved [2, 9] to be accurate and simple in application. Inclusion of electrostatic interactions, however, has encountered the problem of the different (central) character of electrostatic interactions in comparison with the non-central character of the Kihara-like potential. To overcome this difficulty, we recently proposed for fluids of ellipsoidal molecules a version of perturbation theory in which the contribution of electrostatic inter.actions is evaluated via that of a hard Gaussian-overlap (HGO) model with embedded permanent multipole moment(s

Dirac Equation with Spin Symmetry for the Modified P\"oschl-Teller Potential in DD-dimensions

We present solutions of the Dirac equation with spin symmetry for vector and scalar modified P\"oschl-Teller potential within framework of an approximation of the centrifugal term. The relativistic energy spectrum is obtained using the Nikiforov-Uvarov method and the two-component spinor wavefunctions are obtain are in terms of the Jacobi polynomials. It is found that there exist only positive-energy states for bound states under spin symmetry, and the energy levels increase with the dimension and the potential range parameter $\alpha$.Comment: 9 pages and 1tabl

Impacts of El Niño Southern Oscillation and Indian Ocean Dipole on dengue incidence in Bangladesh

Dengue dynamics are driven by complex interactions between hosts, vectors and viruses that are influenced by environmental and climatic factors. Several studies examined the role of El Niño Southern Oscillation (ENSO) in dengue incidence. However, the role of Indian Ocean Dipole (IOD), a coupled ocean atmosphere phenomenon in the Indian Ocean, which controls the summer monsoon rainfall in the Indian region, remains unexplored. Here, we examined the effects of ENSO and IOD on dengue incidence in Bangladesh. According to the wavelet coherence analysis, there was a very weak association between ENSO, IOD and dengue incidence, but a highly significant coherence between dengue incidence and local climate variables (temperature and rainfall). However, a distributed lag nonlinear model (DLNM) revealed that the association between dengue incidence and ENSO or IOD were comparatively stronger after adjustment for local climate variables, seasonality and trend. The estimated effects were nonlinear for both ENSO and IOD with higher relative risks at higher ENSO and IOD. The weak association between ENSO, IOD and dengue incidence might be driven by the stronger effects of local climate variables such as temperature and rainfall. Further research is required to disentangle these effects

Rapid quantification of myocardial fibrosis: a new macro-based automated analysis

Background: Fibrosis is associated with various cardiac pathologies and dysfunction. Current quantification methods are time-consuming and laborious. We describe a semi-automated quantification technique for myocardial fibrosis and validated this using traditional methods

Comparison of quality of life and causes of hospitalization between hemodialysis and peritoneal dialysis patients in China

<p>Abstract</p> <p>Background</p> <p>Hemodialysis (HD) and peritoneal dialysis (PD) are important renal replacement treatment in end stage renal disease (ESRD), but the comparison of quality of life (QOL) and causes of hospitalisation between the two modalities in China is lacking. In the present study, we compared the two modalities in a multi-center study.</p> <p>Subjects and methods</p> <p>Six hundred and fifty four HD and 408 PD patients were investigated from 10 hospitals in China from Sept, 2004 to Jan, 2005. Among the HD patients, there were 360 males and 294 females with a mean age of 57.22 ± 12.49 years (18–88 y). Among PD patients, there were 165 males and 243 females, with a mean age of 61.59 ± 12.65 years (22–89 y). Health related 36 items short form questionnaires (SF-36) were used to assess the quality of life. Hospitalisation data were collected and analyzed.</p> <p>Results</p> <p>SF-36 domains of Body Pain (BP), General Health (GH), Role-Emotional (RE), Social Functioning (SF), Vitality (VT) and Mental Health (MH) were all significantly higher in the PD patients as compared to the HD patients although there was no significant difference in Physical Functioning (PF) and Role-Physical (RP) between the two groups. The two most common causes of hospitalisation in HD patients were cardiovascular disease (39.8%) and pulmonary infection (21.3%), while they were infectious peritonitis (47.6%) and cardiovascular disease (31.9%) in PD patients. The ever hospitalised patients had lower SF-36 scores in the domains of PF, BP, GH, RE, SF, VT and MH as compared to those of non-hospitalised patients.</p> <p>Conclusion</p> <p>Our study indicated that with the current practice in China, PD patients may enjoy better quality of life than their HD counterparts. Our results also showed that the most common cause of hospitalisation was cardiovascular disease in HD patients and peritonitis in PD patients.</p

High grade angiosarcoma arising in fibroadenoma

Primary angiosarcoma of the breast is a rare tumour that account for fewer than 0.05% of all malignant mammary tumours. Angiosarcoma may have an perfidious clinical onset. Radiologic findings are often nonspecific and may appear completely normal in one-third of cases with primary angiosarcoma. The prognosis is usually poor because of the high rates of local recurrence and early development of metastases. Aggressive surgical resection is the mainstay of treatment. The role of adjuvant therapy has not yet been well established

From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification

<p>Abstract</p> <p>Background</p> <p>Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limited resolution for discrimination of bacteria at the species level. In this paper, we approach the species classification problem from a taxonomic point of view. Such a taxonomy or tree is typically obtained by applying clustering algorithms on FAME data or on 16S rRNA gene data. The knowledge gained from the tree can then be used to evaluate FAME-based classifiers, resulting in a novel framework for bacterial species classification.</p> <p>Results</p> <p>In view of learning in a taxonomic framework, we consider two types of trees. First, a FAME tree is constructed with a supervised divisive clustering algorithm. Subsequently, based on 16S rRNA gene sequence analysis, phylogenetic trees are inferred by the NJ and UPGMA methods. In this second approach, the species classification problem is based on the combination of two different types of data. Herein, 16S rRNA gene sequence data is used for phylogenetic tree inference and the corresponding binary tree splits are learned based on FAME data. We call this learning approach 'phylogenetic learning'. Supervised Random Forest models are developed to train the classification tasks in a stratified cross-validation setting. In this way, better classification results are obtained for species that are typically hard to distinguish by a single or flat multi-class classification model.</p> <p>Conclusions</p> <p>FAME-based bacterial species classification is successfully evaluated in a taxonomic framework. Although the proposed approach does not improve the overall accuracy compared to flat multi-class classification, it has some distinct advantages. First, it has better capabilities for distinguishing species on which flat multi-class classification fails. Secondly, the hierarchical classification structure allows to easily evaluate and visualize the resolution of FAME data for the discrimination of bacterial species. Summarized, by phylogenetic learning we are able to situate and evaluate FAME-based bacterial species classification in a more informative context.</p

Estimating Mass Properties of Dinosaurs Using Laser Imaging and 3D Computer Modelling

Body mass reconstructions of extinct vertebrates are most robust when complete to near-complete skeletons allow the reconstruction of either physical or digital models. Digital models are most efficient in terms of time and cost, and provide the facility to infinitely modify model properties non-destructively, such that sensitivity analyses can be conducted to quantify the effect of the many unknown parameters involved in reconstructions of extinct animals. In this study we use laser scanning (LiDAR) and computer modelling methods to create a range of 3D mass models of five specimens of non-avian dinosaur; two near-complete specimens of Tyrannosaurus rex, the most complete specimens of Acrocanthosaurus atokensis and Strutiomimum sedens, and a near-complete skeleton of a sub-adult Edmontosaurus annectens. LiDAR scanning allows a full mounted skeleton to be imaged resulting in a detailed 3D model in which each bone retains its spatial position and articulation. This provides a high resolution skeletal framework around which the body cavity and internal organs such as lungs and air sacs can be reconstructed. This has allowed calculation of body segment masses, centres of mass and moments or inertia for each animal. However, any soft tissue reconstruction of an extinct taxon inevitably represents a best estimate model with an unknown level of accuracy. We have therefore conducted an extensive sensitivity analysis in which the volumes of body segments and respiratory organs were varied in an attempt to constrain the likely maximum plausible range of mass parameters for each animal. Our results provide wide ranges in actual mass and inertial values, emphasizing the high level of uncertainty inevitable in such reconstructions. However, our sensitivity analysis consistently places the centre of mass well below and in front of hip joint in each animal, regardless of the chosen combination of body and respiratory structure volumes. These results emphasize that future biomechanical assessments of extinct taxa should be preceded by a detailed investigation of the plausible range of mass properties, in which sensitivity analyses are used to identify a suite of possible values to be tested as inputs in analytical models

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives