Collapse of the vortex-lattice inductance and shear modulus at the melting transition in untwinned YBa2Cu3O7\rm YBa_2Cu_3O_7

The complex resistivity $\hat{\rho}(\omega)$ of the vortex lattice in an untwinned crystal of 93-K $\rm YBa_2Cu_3O_7$ has been measured at frequencies $\omega/2\pi$ from 100 kHz to 20 MHz in a 2-Tesla field $\bf H\parallel c$, using a 4-probe RF transmission technique that enables continuous measurements versus $\omega$ and temperature $T$. As $T$ is increased, the inductance ${\cal L}_s(\omega) ={\rm Im} \hat{\rho}(\omega)/ \omega$ increases steeply to a cusp at the melting temperature $T_m$, and then undergoes a steep collapse consistent with vanishing of the shear modulus $c_{66}$. We discuss in detail the separation of the vortex-lattice inductance from the `volume' inductance, and other skin-depth effects. To analyze the spectra, we consider a weakly disordered lattice with a low pin density. Close fits are obtained to $\rho_1(\omega)$ over 2 decades in $\omega$. Values of the pinning parameter $\kappa$ and shear modulus $c_{66}$ obtained show that $c_{66}$ collapses by over 4 decades at $T_m$, whereas $\kappa$ remains finite.Comment: 11 pages, 8 figures, Phys. Rev. B, in pres

Consumer E-Service Evaluation in Hong Kong Online Music Subscription Service Industry

This study investigates into factors affecting the success of E-service using a research model grounded on the Updated DeLone and McLean Information System Success Model (DeLone & McLean, 2003). Fourteen factors originated from four constructs, i.e., system quality, information quality, service quality, and vendor dimensions, are included in our research model. Using the online music subscription industry in Hong Kong as the platform of our investigation, we examine the associations between these four constructs and customer preference in the online music subscription service industry in Hong Kong. We collected data from 135 college students from Hong Kong to test our model using the Analytical Hierarchy Process (AHP). We show that each E-business success construct in our model has different levels of importance in E-service success in the online music subscription service industry. Our findings provide decision makers of E-business firms with useful insights to enhance their E-service quality

AI deployment on GBM diagnosis: a novel approach to analyze histopathological images using image feature-based analysis

Background: Glioblastoma (GBM) is one of the most common malignant primary brain tumors, which accounts for 60–70% of all gliomas. Conventional diagnosis and the decision of post-operation treatment plan for glioblastoma is mainly based on the feature-based qualitative analysis of hematoxylin and eosin-stained (H&amp;E) histopathological slides by both an experienced medical technologist and a pathologist. The recent development of digital whole slide scanners makes AI-based histopathological image analysis feasible and helps to diagnose cancer by accurately counting cell types and/or quantitative analysis. However, the technology available for digital slide image analysis is still very limited. This study aimed to build an image feature-based computer model using histopathology whole slide images to differentiate patients with glioblastoma (GBM) from healthy control (HC). Method: Two independent cohorts of patients were used. The first cohort was composed of 262 GBM patients of the Cancer Genome Atlas Glioblastoma Multiform Collection (TCGA-GBM) dataset from the cancer imaging archive (TCIA) database. The second cohort was composed of 60 GBM patients collected from a local hospital. Also, a group of 60 participants with no known brain disease were collected. All the H&amp;E slides were collected. Thirty-three image features (22 GLCM and 11 GLRLM) were retrieved from the tumor volume delineated by medical technologist on H&amp;E slides. Five machine-learning algorithms including decision-tree (DT), extreme-boost (EB), support vector machine (SVM), random forest (RF), and linear model (LM) were used to build five models using the image features extracted from the first cohort of patients. Models built were deployed using the selected key image features for GBM diagnosis from the second cohort (local patients) as model testing, to identify and verify key image features for GBM diagnosis. Results: All five machine learning algorithms demonstrated excellent performance in GBM diagnosis and achieved an overall accuracy of 100% in the training and validation stage. A total of 12 GLCM and 3 GLRLM image features were identified and they showed a significant difference between the normal and the GBM image. However, only the SVM model maintained its excellent performance in the deployment of the models using the independent local cohort, with an accuracy of 93.5%, sensitivity of 86.95%, and specificity of 99.73%. Conclusion: In this study, we have identified 12 GLCM and 3 GLRLM image features which can aid the GBM diagnosis. Among the five models built, the SVM model proposed in this study demonstrated excellent accuracy with very good sensitivity and specificity. It could potentially be used for GBM diagnosis and future clinical application.</p

Distribution of nerve fibers and nerve-immune cell association in mouse spleen revealed by immunofluorescent staining

The central nervous system regulates the immune system through the secretion of hormones from the pituitary gland and other endocrine organs, while the peripheral nervous system (PNS) communicates with the immune system through local nerve-immune cell interactions, including sympathetic/parasympathetic (efferent) and sensory (afferent) innervation to lymphoid tissue/organs. However, the precise mechanisms of this bi-directional crosstalk of the PNS and immune system remain mysterious. To study this kind of bi-directional crosstalk, we performed immunofluorescent staining of neurofilament and confocal microscopy to reveal the distribution of nerve fibers and nerve-immune cell associations inside mouse spleen. Our study demonstrates (i) extensive nerve fibers in all splenic compartments including the splenic nodules, periarteriolar lymphoid sheath, marginal zones, trabeculae, and red pulp; (ii) close associations of nerve fibers with blood vessels (including central arteries, marginal sinuses, penicillar arterioles, and splenic sinuses); (iii) close associations of nerve fibers with various subsets of dendritic cells, macrophages (Mac1+ and F4/80+), and lymphocytes (B cells, T helper cells, and cytotoxic T cells). Our data concerning the extensive splenic innervation and nerve-immune cell communication will enrich our knowledge of the mechanisms through which the PNS affects the cellular- and humoral-mediated immune responses in healthy and infectious/non-infectious states

Effects of fuel composition on high-pressure non-premixed natural gas combustion

The effects of adding ethane or nitrogen on the ignition and combustion of a non-premixed high-pressure methane-air jet have been investigated using fundamental studies in a shock tube and advanced computational modelling. The results are then used to interpret the performance of a pilot-ignited natural gas engine fuelled with similar fuels. The results show that the influence of the additives on the gaseous jet auto-ignition process is relatively small, but that they have a greater effect on the research engine, where both fuels have similar influences on the spatial relationship between the gaseous jet and the pilot flame

Ionizing radiation absorption of vascular surgeons during endovascular procedures

ObjectiveEndovascular procedures have become an integral part of a vascular surgeon’s practice. The exposure of surgeons to ionizing radiation and other safety issues have not been well studied. We investigated the radiation exposure of a team of vascular surgeons in an active endovascular unit and compared yearly dosages absorbed by various body parts among different surgeons. Patients’ radiation exposure was also assessed.MethodsThe radiation absorption of a team of vascular surgeons was prospectively monitored in a 12-month period. During each endovascular procedure, the effective body, eye, and hand radiation doses of all participating surgeons were measured by mini-thermoluminescent dosimeters (TLD) attached at the chest level under a lead apron, at the forehead at eye level, and at the hand. The type of procedure, fluoroscopy machine, fluoroscopy time, and personal and operating theatre radiation protection devices used in each procedure were also recorded. One TLD was attached to the patient’s body near the operative site to measure the patient’s dose. The yearly effective body, eye, and hand dose were compared with the safety limits of radiation for occupational exposure recommended by the International Commission on Radiation Protection (ICRP). The radiation absorption of various body parts per minute of fluoroscopy was compared among different surgeons.ResultsA total of 149 consecutive endovascular procedures were performed, including 30 endovascular aortic repairs (EVAR), 58 arteriograms with and without embolization (AGM), and 61 percutaneous transluminal angioplasty and stent (PTA/S) procedures. The cumulative fluoroscopy time was 1132 minutes. The median yearly effective body, eye, and hand dose for the surgeons were 0.20 mSv (range, 0.13 to 0.27 mSv), 0.19 mSv (range, 0.10 to 0.33 mSv) and 0.99 mSv (0.29 to 1.84 mSv) respectively, which were well below the safety limits of the ICRP. The mean body, eye, and hand dose of the chief surgeon per procedure were highest for EVAR. A significant discrepancy was observed for the average hand dose per minute of fluoroscopy among different surgeons. The mean radiation absorption of patients who underwent EVAR, AGM, and PTA/S was 12.7 mSv, 13.6 mSv, and 3.4 mSv, respectively.ConclusionWith current radiation protection practice, the radiation absorbed by vascular surgeons with a high endovascular workload did not exceed the safety limits recommended by ICRP. Variations in practice, however, can result in significant discrepancy of radiation absorption between surgeons

Classification of multipartite entangled states by multidimensional determinants

We find that multidimensional determinants "hyperdeterminants", related to entanglement measures (the so-called concurrence or 3-tangle for the 2 or 3 qubits, respectively), are derived from a duality between entangled states and separable states. By means of the hyperdeterminant and its singularities, the single copy of multipartite pure entangled states is classified into an onion structure of every closed subset, similar to that by the local rank in the bipartite case. This reveals how inequivalent multipartite entangled classes are partially ordered under local actions. In particular, the generic entangled class of the maximal dimension, distinguished as the nonzero hyperdeterminant, does not include the maximally entangled states in Bell's inequalities in general (e.g., in the $n \geq 4$ qubits), contrary to the widely known bipartite or 3-qubit cases. It suggests that not only are they never locally interconvertible with the majority of multipartite entangled states, but they would have no grounds for the canonical n-partite entangled states. Our classification is also useful for the mixed states.Comment: revtex4, 10 pages, 4 eps figures with psfrag; v2 title changed, 1 appendix added, to appear in Phys. Rev.