Value of micro-CT for monitoring spinal microvascular changes after chronic spinal cord compression

published_or_final_versio

Microstructures and resistivity of cuprate/manganite bilayer deposited on SrTiO3 substrate

Thin Yba[SUB2]Cu[SUB3]O[SUB7-δ/La[SUB0.67]Ca[SUB0.33]MnO[SUB3] (YBCO/LCMO) films were grown on SrTiO[SUB3](STO)substrates by magnetron sputtering technique. The microstructures of the bilayers were characterized and a standard four-probe technique was applied to measure the resistivity of the samples. The interdiffusions at the YBCO/LCMO and LCMO/STO interfaces formed two transient layers with the thickness of about 3 and 2 nm, respectively. All the bilayers were well textured along the c axis. At low temperature, the superconductivity can only be observed when the thickness of YBCO is more than 25 nm. When the thickness of YBCO is less than 8 nm, the bilayers show only ferromagnetism. The superconductivity and ferromagnetism perhaps coexist in the bilayer with the YBCO thickness of 12.5 nm. These interesting properties are related to the interaction between spin polarized electrons in the manganites and the cooper pairs in the cuprates. © 2003 American Institute of Physics.published_or_final_versio

Bayesian network approach to fault diagnosis of a hydroelectric generation system

This study focuses on the fault diagnosis of a hydroelectric generation system with hydraulic-mechanical-electric structures. To achieve this analysis, a methodology combining Bayesian network approach and fault diagnosis expert system is presented, which enables the time-based maintenance to transform to the condition-based maintenance. First, fault types and the associated fault characteristics of the generation system are extensively analyzed to establish a precise Bayesian network. Then, the Noisy-Or modeling approach is used to implement the fault diagnosis expert system, which not only reduces node computations without severe information loss but also eliminates the data dependency. Some typical applications are proposed to fully show the methodology capability of the fault diagnosis of the hydroelectric generation system

Realizing and characterizing chiral photon flow in a circuit quantum electrodynamics necklace

Gauge theory plays the central role in modern physics. Here we propose a scheme of implementing artificial Abelian gauge fields via the parametric conversion method in a necklace of superconducting transmission line resonators (TLRs) coupled by superconducting quantum interference devices (SQUIDs). The motivation is to synthesize an extremely strong effective magnetic field for charge-neutral bosons which can hardly be achieved in conventional solid-state systems. The dynamic modulations of the SQUIDs can induce effective magnetic fields for the microwave photons in the TLR necklace through the generation of the nontrivial hopping phases of the photon hopping between neighboring TLRs. To demonstrate the synthetic magnetic field, we study the realization and detection of the chiral photon flow dynamics in this architecture under the influence of decoherence. Taking the advantages of its simplicity and flexibility, this parametric scheme is feasible with state-of-the-art technology and may pave an alternative way for investigating the gauge theories with superconducting quantum circuits. We further propose a quantitative measure for the chiral property of the photon flow. Beyond the level of qualitative description, the dependence of the chiral flow on external pumping parameters and cavity decay is characterized

Public health and medical care for the world's factory: China's Pearl River Delta Region

While the growth of urbanization, worldwide, has improved the lives of migrants from the hinterland, it also raises health risks related to population density, concentrated poverty and the transmission of infectious disease. Will megacity regions evolve into socially infected breeding grounds for the rapid transmission of disease, or can they become critical spatial entities for the protection and promotion of population health? We address this question for the Pearl River Delta Region (PRD) based on recent data from Chinese sources, and on the experience of how New York, Greater London, Tokyo and Paris have grappled with the challenges of protecting population health and providing their populations with access to health care services. In some respects, there are some important lessons from comparative experience for PRD, notably the importance of covering the entire population for health care services and targeting special programs for those at highest risk for disease. In other respects, PRD's growth rate and sheer scale make it a unique megacity region that already faces new challenges and will require new solutions

Immunosuppression and the Risk of Post-Transplant Malignancy Among Cadaveric First Kidney Transplant Recipients

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73619/1/j.1600-6135.2003.00274.x.pd

Training Auto-encoder-based Optimizers for Terahertz Image Reconstruction

Terahertz (THz) sensing is a promising imaging technology for a wide variety of different applications. Extracting the interpretable and physically meaningful parameters for such applications, however, requires solving an inverse problem in which a model function determined by these parameters needs to be fitted to the measured data. Since the underlying optimization problem is nonconvex and very costly to solve, we propose learning the prediction of suitable parameters from the measured data directly. More precisely, we develop a model-based autoencoder in which the encoder network predicts suitable parameters and the decoder is fixed to a physically meaningful model function, such that we can train the encoding network in an unsupervised way. We illustrate numerically that the resulting network is more than 140 times faster than classical optimization techniques while making predictions with only slightly higher objective values. Using such predictions as starting points of local optimization techniques allows us to converge to better local minima about twice as fast as optimization without the network-based initialization.Comment: This is a pre-print of a conference paper published in German Conference on Pattern Recognition (GCPR) 201

Semi-analytical approach to magnetized temperature autocorrelations

The cosmic microwave background (CMB) temperature autocorrelations, induced by a magnetized adiabatic mode of curvature inhomogeneities, are computed with semi-analytical methods. As suggested by the latest CMB data, a nearly scale-invariant spectrum for the adiabatic mode is consistently assumed. In this situation, the effects of a fully inhomogeneous magnetic field are scrutinized and constrained with particular attention to harmonics which are relevant for the region of Doppler oscillations. Depending on the parameters of the stochastic magnetic field a hump may replace the second peak of the angular power spectrum. Detectable effects on the Doppler region are then expected only if the magnetic power spectra have quasi-flat slopes and typical amplitude (smoothed over a comoving scale of Mpc size and redshifted to the epoch of gravitational collapse of the protogalaxy) exceeding 0.1 nG. If the magnetic energy spectra are bluer (i.e. steeper in frequency) the allowed value of the smoothed amplitude becomes, comparatively, larger (in the range of 20 nG). The implications of this investigation for the origin of large-scale magnetic fields in the Universe are discussed. Connections with forthcoming experimental observations of CMB temperature fluctuations are also suggested and partially explored.Comment: 40 pages, 13 figure

Expressing one’s feelings and listening to others increases emotional intelligence: a pilot study of Asian medical students

<p>Background: There has been considerable interest in Emotional Intelligence (EI) in undergraduate medical education, with respect to student selection and admissions, health and well-being and academic performance. EI is a significant component of the physician-patient relationship. The emotional well-being of the physician is, therefore, a significant component in patient care. The aim is to examine the measurement of TEIQue-SF in Asian medical students and to explore how the practice of listening to the feelings of others and expressing one’s own feelings influences an individual’s EI, set in the context of the emotional well-being of a medical practitioner.</p> <p>Methods: A group of 183 international undergraduate medical students attended a half-day workshop (WS) about mental-health and well-being. They completed a self-reported measure of EI on three occasions, pre- and post-workshop, and a 1-year follow-up.</p> <p>Result: The reliability of TEIQue-SF was high and the reliabilities of its four factors were acceptable. There were strong correlations between the TEIQue-SF and personality traits. A paired t-test indicated significant positive changes after the WS for all students (n=181, p= .014), male students (n=78, p= .015) and non-Japanese students (n=112, p= .007), but a repeated measures analysis showed that one year post-workshop there were significant positive changes for all students (n=55, p= .034), female students (n=31, p= .007), especially Japanese female students (n=13, p= .023). Moreover, 80% of the students reported that they were more attentive listeners, and 60% agreed that they were more confident in dealing with emotional issues, both within themselves and in others, as a result of the workshop.</p> <p>Conclusion: This study found the measurement of TEIQue-SF is appropriate and reliable to use for Asian medical students. The mental health workshop was helpful to develop medical students’ EI but showed different results for gender and nationality. The immediate impact on the emotional awareness of individuals was particularly significant for male students and the non-Japanese group. The impact over the long term was notable for the significant increase in EI for females and Japanese. Japanese female students were more conscious about emotionality. Emotion-driven communication exercises might strongly influence the development of students’ EI over a year.</p&gt

A Pose-Based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants

The early diagnosis of cerebral palsy is an area which has recently seen significant multi-disciplinary research. Diagnostic tools such as the General Movements Assessment (GMA), have produced some very promising results. However, the prospect of automating these processes may improve accessibility of the assessment and also enhance the understanding of movement development of infants. Previous works have established the viability of using pose-based features extracted from RGB video sequences to undertake classification of infant body movements based upon the GMA. In this paper, we propose a series of new and improved features, and a feature fusion pipeline for this classification task. We also introduce the RVI-38 dataset, a series of videos captured as part of routine clinical care. By utilising this challenging dataset we establish the robustness of several motion features for classification, subsequently informing the design of our proposed feature fusion framework based upon the GMA. We evaluate our proposed framework’s classification performance using both the RVI-38 dataset and the publicly available MINI-RGBD dataset. We also implement several other methods from the literature for direct comparison using these two independent datasets. Our experimental results and feature analysis show that our proposed pose-based method performs well across both datasets. The proposed features afford us the opportunity to include finer detail than previous methods, and further model GMA specific body movements. These new features also allow us to take advantage of additional body-part specific information as a means of improving the overall classification performance, whilst retaining GMA relevant, interpretable, and shareable features