Critical Currents of Josephson-Coupled Wire Arrays

We calculate the current-voltage characteristics and critical current I_c^{array} of an array of Josephson-coupled superconducting wires. The array has two layers, each consisting of a set of parallel wires, arranged at right angles, such that an overdamped resistively-shunted junction forms wherever two wires cross. A uniform magnetic field equal to f flux quanta per plaquette is applied perpendicular to the layers. If f = p/q, where p and q are mutually prime integers, I_c^{array}(f) is found to have sharp peaks when q is a small integer. To an excellent approximation, it is found in a square array of n^2 plaquettes, that I_c^{array}(f) \propto (n/q)^{1/2} for sufficiently large n. This result is interpreted in terms of the commensurability between the array and the assumed q \times q unit cell of the ground state vortex lattice.Comment: 4 pages, 4 figure

The Linear Theory Power Spectrum from the Lyman-alpha Forest in the Sloan Digital Sky Survey

We analyze the SDSS Ly-alpha forest P_F(k,z) measurement to determine the linear theory power spectrum. Our analysis is based on fully hydrodynamic simulations, extended using hydro-PM simulations. We account for the effect of absorbers with damping wings, which leads to an increase in the slope of the linear power spectrum. We break the degeneracy between the mean level of absorption and the linear power spectrum without significant use of external constraints. We infer linear theory power spectrum amplitude Delta^2_L(k_p=0.009s/km,z_p=3.0)=0.452_{-0.057-0.116}^{+0.069+0.141} and slope n_eff=-2.321_{-0.047-0.102}^{+0.055+0.131} (possible systematic errors are included through nuisance parameters in the fit - a factor >~5 smaller errors would be obtained on both parameters if we ignored modeling uncertainties). The errors are correlated and not perfectly Gaussian, so we provide a chi^2 table to accurately describe the results. The result corresponds to sigma_8=0.85, n=0.94, for a LCDM model with Omega_m=0.3, Omega_b=0.04, and h=0.7, but is most useful in a combined fit with the CMB. The inferred curvature of the linear power spectrum and the evolution of its amplitude and slope with redshift are consistent with expectations for LCDM models, with the evolution of the slope, in particular, being tightly constrained. We use this information to constrain systematic contamination, e.g., fluctuations in the UV background. This paper should serve as a starting point for more work to refine the analysis, including technical improvements such as increasing the size and number of the hydrodynamic simulations, and improvements in the treatment of the various forms of feedback from galaxies and quasars.Comment: Improved presentation, including fit results for (z). Simple code to produce LyaF chi^2 given linear power spectrum available at: http://www.cita.utoronto.ca/~pmcdonal/code.htm

The Lyman-alpha Forest Power Spectrum from the Sloan Digital Sky Survey

We measure the power spectrum, P_F(k,z), of the transmitted flux in the Ly-alpha forest using 3035 high redshift quasar spectra from the Sloan Digital Sky Survey. This sample is almost two orders of magnitude larger than any previously available data set, yielding statistical errors of ~0.6% and ~0.005 on, respectively, the overall amplitude and logarithmic slope of P_F(k,z). This unprecedented statistical power requires a correspondingly careful analysis of the data and of possible systematic contaminations in it. For this purpose we reanalyze the raw spectra to make use of information not preserved by the standard pipeline. We investigate the details of the noise in the data, resolution of the spectrograph, sky subtraction, quasar continuum, and metal absorption. We find that background sources such as metals contribute significantly to the total power and have to be subtracted properly. We also find clear evidence for SiIII correlations with the Ly-alpha forest and suggest a simple model to account for this contribution to the power. While it is likely that our newly developed analysis technique does not eliminate all systematic errors in the P_F(k,z) measurement below the level of the statistical errors, our tests indicate that any residual systematics in the analysis are unlikely to affect the inference of cosmological parameters from P_F(k,z). These results should provide an essential ingredient for all future attempts to constrain modeling of structure formation, cosmological parameters, and theories for the origin of primordial fluctuations.Comment: 92 pages, 45 of them figures, submitted to ApJ, data available at http://feynman.princeton.edu/~pmcdonal/LyaF/sdss.htm

Anion height as a controlling parameter for the superconductivity in iron pnictides and cuprates

Both families of high $T_c$ superconductors, iron pnictides and cuprates, exhibit material dependence of superconductivity. Here, we study its origin within the spin fluctuation pairing theory based on multiorbital models that take into account realistic band structures. For pnictides, we show that the presence and absence of Fermi surface pockets is sensitive to the pnictogen height measured from the iron plane due to the multiorbital nature of the system, which is reflected to the nodeless/nodal form of the superconducting gap and $T_c$. Surprisingly, even for the cuprates, which is conventionally modeled by a single orbital model, the multiorbital band structure is shown to play a crucial role in the material dependence of superconductivity. In fact, by adopting a two orbital model that considers the $d_{z^2}$ orbital on top of the $d_{x^2-y^2}$ orbital, we can resolve a long standing puzzle of why the single layered Hg cuprate have much higher $T_c$ than the La cuprate. Interestingly, here again the apical oxygen height measured from the CuO$_2$ plane plays an important role in determining the relative energy difference between $d_{x^2-y^2}$ and $d_{z^2}$ orbitals, thereby strongly affecting the superconductivity.Comment: 8 pages, 7 figures, submitted as Proceedings of SNS201

Seg2Reg: Differentiable 2D Segmentation to 1D Regression Rendering for 360 Room Layout Reconstruction

State-of-the-art single-view 360-degree room layout reconstruction methods formulate the problem as a high-level 1D (per-column) regression task. On the other hand, traditional low-level 2D layout segmentation is simpler to learn and can represent occluded regions, but it requires complex post-processing for the targeting layout polygon and sacrifices accuracy. We present Seg2Reg to render 1D layout depth regression from the 2D segmentation map in a differentiable and occlusion-aware way, marrying the merits of both sides. Specifically, our model predicts floor-plan density for the input equirectangular 360-degree image. Formulating the 2D layout representation as a density field enables us to employ `flattened' volume rendering to form 1D layout depth regression. In addition, we propose a novel 3D warping augmentation on layout to improve generalization. Finally, we re-implement recent room layout reconstruction methods into our codebase for benchmarking and explore modern backbones and training techniques to serve as the strong baseline. Our model significantly outperforms previous arts. The code will be made available upon publication

Finite precision measurement nullifies the Kochen-Specker theorem

Only finite precision measurements are experimentally reasonable, and they cannot distinguish a dense subset from its closure. We show that the rational vectors, which are dense in S^2, can be colored so that the contradiction with hidden variable theories provided by Kochen-Specker constructions does not obtain. Thus, in contrast to violation of the Bell inequalities, no quantum-over-classical advantage for information processing can be derived from the Kochen-Specker theorem alone.Comment: 7 pages, plain TeX; minor corrections, interpretation clarified, references update

Caveolin-1 is Associated with Tumor Progression and Confers a Multi-Modality Resistance Phenotype in Pancreatic Cancer

Caveolin-1 (Cav-1) is a 21 kDa protein enriched in caveolae, and has been implicated in oncogenic cell transformation, tumorigenesis, and metastasis. We explored roles for Cav-1 in pancreatic cancer (PC) prognostication, tumor progression, resistance to therapy, and whether targeted downregulation could lead to therapeutic sensitization. Cav-1 expression was assessed in cell lines, mouse models, and patient samples, and knocked down in order to compare changes in proliferation, invasion, migration, response to chemotherapy and radiation, and tumor growth. We found Cav-1 is overexpressed in human PC cell lines, mouse models, and human pancreatic tumors, and is associated with worse tumor grade and clinical outcomes. In PC cell lines, disruption/depletion of caveolae/Cav-1 reduces proliferation, colony formation, and invasion. Radiation and chemotherapy up-regulate Cav-1 expression, while Cav-1 depletion induces both chemosensitization and radiosensitization through altered apoptotic and DNA repair signaling. In vivo, Cav-1 depletion significantly attenuates tumor initiation and growth. Finally, Cav-1 depletion leads to altered JAK/STAT, JNK, and Src signaling in PC cells. Together, higher Cav-1 expression is correlated with worse outcomes, is essential for tumor growth and invasion (both in vitro and in vivo), is responsible for promoting resistance to therapies, and may serve as a prognostic/predictive biomarker and target in PC

Instantaneous 3D EEG Signal Analysis Based on Empirical Mode Decomposition and the Hilbert–Huang Transform Applied to Depth of Anaesthesia

Depth of anaesthesia (DoA) is an important measure for assessing the degree to which the central nervous system of a patient is depressed by a general anaesthetic agent, depending on the potency and concentration with which anaesthesia is administered during surgery. We can monitor the DoA by observing the patient’s electroencephalography (EEG) signals during the surgical procedure. Typically high frequency EEG signals indicates the patient is conscious, while low frequency signals mean the patient is in a general anaesthetic state. If the anaesthetist is able to observe the instantaneous frequency changes of the patient’s EEG signals during surgery this can help to better regulate and monitor DoA, reducing surgical and post-operative risks. This paper describes an approach towards the development of a 3D real-time visualization application which can show the instantaneous frequency and instantaneous amplitude of EEG simultaneously by using empirical mode decomposition (EMD) and the Hilbert–Huang transform (HHT). HHT uses the EMD method to decompose a signal into so-called intrinsic mode functions (IMFs). The Hilbert spectral analysis method is then used to obtain instantaneous frequency data. The HHT provides a new method of analyzing non-stationary and nonlinear time series data. We investigate this approach by analyzing EEG data collected from patients undergoing surgical procedures. The results show that the EEG differences between three distinct surgical stages computed by using sample entropy (SampEn) are consistent with the expected differences between these stages based on the bispectral index (BIS), which has been shown to be quantifiable measure of the effect of anaesthetics on the central nervous system. Also, the proposed filtering approach is more effective compared to the standard filtering method in filtering out signal noise resulting in more consistent results than those provided by the BIS. The proposed approach is therefore able to distinguish between key operational stages related to DoA, which is consistent with the clinical observations. SampEn can also be viewed as a useful index for evaluating and monitoring the DoA of a patient when used in combination with this approach

Early objective response to avelumab treatment is associated with improved overall survival in patients with metastatic Merkel cell carcinoma

Background: Response rates are primary endpoints in many oncology trials; however, correlation with overall survival (OS) is not uniform across cancer types, treatments, or lines of therapy. This study explored the association between objective response (OR) and OS in patients with chemotherapy-refractory metastatic Merkel cell carcinoma who received avelumab (anti-PD-L1). Methods: Eighty-eight patients enrolled in JAVELIN Merkel 200 (part A; NCT02155647) received i.v. avelumab 10 mg/kg every 2 weeks until confirmed progression, unacceptable toxicity, or withdrawal. Using conditional landmark analyses, we compared OS in patients with and without confirmed OR (RECIST v1.1). We applied a Cox model that included OR as a time-varying covariate and adjusted for age, visceral disease, and number of previous therapies. Results: Twenty-nine patients had confirmed OR; 20 by study week 7 and 7 more between study weeks 7 and 13. Survival probabilities 18 months after treatment initiation were 90% [95% confidence interval (CI) 65.6-97.4] in patients with OR at week 7 and 26.2% (95% CI 15.7-37.8) in patients without OR but who were alive at week 7. Median OS was not reached in patients with OR and was 8.8 months (95% CI 6.4-12.9) in patients without. Similar results were observed for the week 13 landmark. The adjusted Cox model showed OR was associated with a 95% risk reduction of death [hazard ratio 0.052 (95% CI 0.018-0.152)] compared with a nonresponse. Conclusions: Patients with OR by 7 or 13 weeks had significantly longer OS than patients without, confirming that early OR is an endpoint of major importance