Field-Trial of Machine Learning-Assisted Quantum Key Distribution (QKD) Networking with SDN

We demonstrated, for the first time, a machine-learning method to assist the coexistence between quantum and classical communication channels. Software-defined networking was used to successfully enable the key generation and transmission over a city and campus network

Thermocatalytic syntheses of highly defective hybrid nano-catalysts for photocatalytic hydrogen evolution

Defects play important roles in many catalytic processes, particularly for photocatalytic processes in semiconductors as they can alter the band structures and affect the excited electron–hole recombination pathways/lifetimes of semiconductors. In this report, we described the development of a facile route to the production of highly defective photocatalysts. Firstly, organic species were bound onto the surface of a metal oxide semiconductor catalyst, followed by a relatively low temperature ageing in N2, to remove the organics and to attract oxygen molecules from the surface, generating oxygen vacancies. In particular, we introduced a co-catalyst during the syntheses, which acted as a thermocatalyst to promote full oxidation of the organics, leaving more oxygen vacancies at the surface and to form intimate heterojunctions with host-catalysts to further drive the photocatalytic hydrogen evolution. The hydrogen evolution rate for our developed NiO–TiO2 defective heterojunctions in a sacrificial system was measured at ca. 1.41 mmol g−1 h−1, which was much higher than those of comparable catalysts reported in the literature (that generally display hydrogen evolution rates <0.4 mmol g−1 h−1). Computational simulation, together with other analytical techniques, suggested that the generated surface oxygen vacancies could induce a series of impurity energy levels within the VBM and CBM of TiO2 that narrowed the electron transmission gap in the TiO2 and acted as active sites for the reaction between adsorbed H2O and photoinduced trapped electrons to produce H2

Auto-tracking system for human lumbar motion analysis

Previous lumbar motion analyses suggest the usefulness of quantitatively characterizing spine motion. However, the application of such measurements is still limited by the lack of user-friendly automatic spine motion analysis systems. This paper describes an automatic analysis system to measure lumbar spine disorders that consists of a spine motion guidance device, an X-ray imaging modality to acquire digitized video fluoroscopy (DVF) sequences and an automated tracking module with a graphical user interface (GUI). DVF sequences of the lumbar spine are recorded during flexion-extension under a guidance device. The automatic tracking software utilizing a particle filter locates the vertebra-of-interest in every frame of the sequence, and the tracking result is displayed on the GUI. Kinematic parameters are also extracted from the tracking results for motion analysis. We observed that, in a bone model test, the maximum fiducial error was 3.7%, and the maximum repeatability error in translation and rotation was 1.2% and 2.6%, respectively. In our simulated DVF sequence study, the automatic tracking was not successful when the noise intensity was greater than 0.50. In a noisy situation, the maximal difference was 1.3 mm in translation and 1° in the rotation angle. The errors were calculated in translation (fiducial error: 2.4%, repeatability error: 0.5%) and in the rotation angle (fiducial error: 1.0%, repeatability error: 0.7%). However, the automatic tracking software could successfully track simulated sequences contaminated by noise at a density ≤ 0.5 with very high accuracy, providing good reliability and robustness. A clinical trial with 10 healthy subjects and 2 lumbar spondylolisthesis patients were enrolled in this study. The measurement with auto-tacking of DVF provided some information not seen in the conventional X-ray. The results proposed the potential use of the proposed system for clinical applications. © 2011 - IOS Press and the authors. All rights reserved.postprin

Study of outgoing longwave radiation anomalies associated with Haiti earthquake

The paper presents an analysis by using the methods of Eddy field calculation mean and wavelet maxima to detect seismic anomalies within the outgoing longwave radiation (OLR) data based on time and space. The distinguishing feature of the method of Eddy field calculation mean is that we can calculate "the total sum of the difference value" of "the measured value" between adjacent points, which could highlight the singularity within data. The identified singularities are further validated by wavelet maxima, which using wavelet transformations as data mining tools by computing the maxima that can be used to identify obvious anomalies within OLR data. The two methods has been applied to carry out a comparative analysis of OLR data associated with the earthquake recently occurred in Haiti on 12 January 2010. Combining with the tectonic explanation of spatial and temporal continuity of the abnormal phenomena, the analyzed results have indicated a number of singularities associated with the possible seismic anomalies of the earthquake and from the comparative experiments and analyses by using the two methods, which follow the same time and space, we conclude that the singularities observed from 19 to 24 December 2009 could be the earthquake precursor of Haiti earthquake

Far-infrared optical properties of the pyrochlore spin ice compound Dy2Ti2O4

Near normal incident far-infrared reflectivity spectra of [111] dysprosium titanate (Dy2Ti2O4) single crystal have been measured at different temperatures. Seven phonon modes (eight at low temperature) are identified at frequency below 1000 cm-1. Optical conductivity spectra are obtained by fitting all the reflectivity spectra with the factorized form of the dielectric function. Both the Born effective charges and the static optical primitivity are found to increase with decreasing temperature. Moreover, phonon linewidth narrowering and phonon modes shift with decreasing temperature are also observed, which may result from enhanced charge localization. The redshift of several low frequency modes is attributed to the spin-phonon coupling. All observed optical properties can be explained within the framework of nearest neighbor ferromagnetic(FM) spin ice model

Increased expression of programmed death ligand 1 (PD-L1) in human pituitary tumors

PURPOSE: Subsets of pituitary tumors exhibit an aggressive clinical courses and recur despite surgery, radiation, and chemotherapy. Because modulation of the immune response through inhibition of T-cell checkpoints has led to durable clinical responses in multiple malignancies, we explored whether pituitary adenomas express immune-related biomarkers that could suggest suitability for immunotherapy. Specifically, programmed death ligand 1 (PD-L1) has emerged as a potential biomarker whose expression may portend more favorable responses to immune checkpoint blockade therapies. We thus investigated the expression of PD-L1 in pituitary adenomas. METHODS: PD-L1 RNA and protein expression were evaluated in 48 pituitary tumors, including functioning and non-functioning adenomas as well as atypical and recurrent tumors. Tumor infiltrating lymphocyte populations were also assessed by immunohistochemistry. RESULTS: Pituitary tumors express variable levels of PD-L1 transcript and protein. PD-L1 RNA and protein expression were significantly increased in functioning (growth hormone and prolactin-expressing) pituitary adenomas compared to non-functioning (null cell and silent gonadotroph) adenomas. Moreover, primary pituitary adenomas harbored higher levels of PD-L1 mRNA compared to recurrent tumors. Tumor infiltrating lymphocytes were observed in all pituitary tumors and were positively correlated with increased PD-L1 expression, particularly in the functional subtypes. CONCLUSIONS: Human pituitary adenomas harbor PD-L1 across subtypes, with significantly higher expression in functioning adenomas compared to non-functioning adenomas. This expression is accompanied by the presence of tumor infiltrating lymphocytes. These findings suggest the existence of an immune response to pituitary tumors and raise the possibility of considering checkpoint blockade immunotherapy in cases refractory to conventional management

Learning Optimal Deep Projection of 18^{18}F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes

Several diseases of parkinsonian syndromes present similar symptoms at early stage and no objective widely used diagnostic methods have been approved until now. Positron emission tomography (PET) with $^{18}$F-FDG was shown to be able to assess early neuronal dysfunction of synucleinopathies and tauopathies. Tensor factorization (TF) based approaches have been applied to identify characteristic metabolic patterns for differential diagnosis. However, these conventional dimension-reduction strategies assume linear or multi-linear relationships inside data, and are therefore insufficient to distinguish nonlinear metabolic differences between various parkinsonian syndromes. In this paper, we propose a Deep Projection Neural Network (DPNN) to identify characteristic metabolic pattern for early differential diagnosis of parkinsonian syndromes. We draw our inspiration from the existing TF methods. The network consists of a (i) compression part: which uses a deep network to learn optimal 2D projections of 3D scans, and a (ii) classification part: which maps the 2D projections to labels. The compression part can be pre-trained using surplus unlabelled datasets. Also, as the classification part operates on these 2D projections, it can be trained end-to-end effectively with limited labelled data, in contrast to 3D approaches. We show that DPNN is more effective in comparison to existing state-of-the-art and plausible baselines.Comment: 8 pages, 3 figures, conference, MICCAI DLMIA, 201

Infrared response of ordered polarons in layered perovskites

We report on the infrared absorption spectra of three oxides where charged superlattices have been recently observed in diffraction experiments. In La$_{1.67}$Sr$_{0.33}$NiO$_4$, polaron localization is found to suppress the low-energy conductivity through the opening of a gap and to split the $E_{2u}$-$A_{2u}$ vibrational manifold of the oxygen octahedra. Similar effects are detected in Sr$_{1.5}$La$_{0.5}$MnO$_4$ and in La$_2$NiO$_{4+y}$, with peculiar differences related to the type of charge ordering.Comment: File latex, 11 p. + 3 Figures, to appear on Phys. Rev. B (Rapid Commun.), 1 Oct. 1996. The figures will be faxed upon request. E-mail:[email protected] Fax: +39-6-446315