Associated Charmonium Production in Low Energy p-pbar Annihilation

The QCD mechanisms underlying the exclusive strong decays and hadronic production amplitudes of charmonium remain poorly understood, despite decades of study and an increasingly detaled body of experimental information. One set of hadronic channels of special interest are those that include baryon-antibaryon states. These are being investigated experimentally at BES and CLEO-c in terms of their baryon resonance content, and are also of interest for the future PANDA experiment, in which charmonium and charmonium hybrids will be produced in p-pbar annihilation in association with light mesons. In this paper we develop a simple initial-state light meson emission model of the near-threshold associated charmonium production processes p pbar -> pi0 ccbar, and evaluate the differential and total cross sections for these reactions in this model. (Here we consider the ccbar states eta_c, J/psi, psi', chi_0 and chi_1.) The predicted near-threshold cross section for p pbar -> pi0 J/psi is found to be numerically similar to two previous theoretical estimates, and is roughly comparable to the (sparse) existing data for this process. The theoretical charmonium angular distributions predicted by this model are far from isotropic, which may be of interest for PANDA detector design studies.Comment: 6 pages, 4 figures, uses graphicx and feynm

Simulating California reservoir operation using the classification and regression-tree algorithm combined with a shuffled cross-validation scheme

The controlled outflows from a reservoir or dam are highly dependent on the decisions made by the reservoir operators, instead of a natural hydrological process. Difference exists between the natural upstream inflows to reservoirs and the controlled outflows from reservoirs that supply the downstream users. With the decision maker's awareness of changing climate, reservoir management requires adaptable means to incorporate more information into decision making, such as water delivery requirement, environmental constraints, dry/wet conditions, etc. In this paper, a robust reservoir outflow simulation model is presented, which incorporates one of the well-developed data-mining models (Classification and Regression Tree) to predict the complicated human-controlled reservoir outflows and extract the reservoir operation patterns. A shuffled cross-validation approach is further implemented to improve CART's predictive performance. An application study of nine major reservoirs in California is carried out. Results produced by the enhanced CART, original CART, and random forest are compared with observation. The statistical measurements show that the enhanced CART and random forest overperform the CART control run in general, and the enhanced CART algorithm gives a better predictive performance over random forest in simulating the peak flows. The results also show that the proposed model is able to consistently and reasonably predict the expert release decisions. Experiments indicate that the release operation in the Oroville Lake is significantly dominated by SWP allocation amount and reservoirs with low elevation are more sensitive to inflow amount than others

I=2 Two-Pion Wave Function and Scattering Phase Shift

We calculate a two-pion wave function for the I=2 $S$-wave two-pion system with a finite scattering momentum and estimate the interaction range between two pions, which allows us to examine the validity of a necessary condition for the finite size formula presented by Rummukainen and Gottlieb. We work in the quenched approximation employing the plaquette gauge action for gluons and the improved Wilson action for quarks at $1/a=1.63 {\rm GeV}$ on $32^3\times 120$ lattice. The quark masses are chosen to give $m_\pi = 0.420$, 0.488 and $0.587 {\rm GeV}$. We find that the energy dependence of the interaction range is small and the necessary condition is satisfied for our range of the quark mass and the scattering momentum, $k \le 0.16 {\rm GeV}$. We also find that the scattering phase shift can be obtained with a smaller statistical error from the two-pion wave function than from the two-pion time correlator.Comment: 23 pages, 7 figures, added a reference (Phys.Rev.D73:054503,2006) in v

Asteroseismology of the δ\delta Scuti star HD 50844

Aims. We aim to probe the internal structure and investigate more detailed information of the $\delta$ Scuti star HD 50844 with asteroseismology. Methods. We analyse the observed frequencies of the $\delta$ Scuti star HD 50844 obtained by Balona (2014), and search for possible multiplets based on the rotational splitting law of g-mode. We tried to disentangle the frequency spectra of HD 50844 by means of the rotational splitting only. We then compare them with theoretical pulsation modes, which correspond to stellar evolutionary models with various sets of initial metallicity and stellar mass, to find the best-fitting model. Results. There are three multiplets including two complete triplets and one incomplete quintuplet, in which mode identifications for spherical harmonic degree $l$ and azimuthal number $m$ are unique. The corresponding rotational period of HD 50844 is found to be 2.44$^{+0.13}_{-0.08}$ days. The physical parameters of HD 50844 are well limited in a small region by three modes identified as nonradial ones ($f_{11}$, $f_{22}$, and $f_{29}$) and by the fundamental radial mode ($f_{4}$). Our results show that the three nonradial modes ($f_{11}$, $f_{22}$, and $f_{29}$) are all mixed modes, which mainly represent the property of the helium core. The fundamental radial mode ($f_{4}$) mainly represents the property of the stellar envelope. In order to fit these four pulsation modes, both the helium core and the stellar envelope must be matched to the actual structure of HD 50844. Finally, the mass of the helium core of HD 50844 is estimated to be 0.173 $\pm$ 0.004 $M_{\odot}$ for the first time. The physical parameters of HD 50844 are determined to be $M=$ 1.81 $\pm$ 0.01 $M_{\odot}$, $Z=$ 0.008 $\pm$ 0.001. $T_{\rm eff}=$ 7508 $\pm$ 125 K, log$g=$ 3.658 $\pm$ 0.004, $R=$ 3.300 $\pm$ 0.023 $R_{\odot}$, $L=$ 30.98 $\pm$ 2.39 $L_{\odot}$.Comment: 11 pages, 7 figures, 6 tables, accepted for publication in A&

Double-layer Perfect Metamaterial Absorber and Its Application for RCS Reduction of Antenna

To reduce the radar cross section (RCS) of a circularly polarized (CP) tilted beam antenna, a double-layer perfect metamaterial absorber (DLPMA) in the microwave frequency is proposed. The DLPMA exhibits a wider band by reducing the distance between the three absorption peaks. Absorbing characteristics are analyzed and the experimental results demonstrate that the proposed absorber works well from 5.95 GHz to 6.86 GHz (relative bandwidth 14.1%) with the thickness of 0.5 mm. Then, the main part of perfect electric conductor ground plane of the CP tilted beam antenna is covered by the DLPMA. Simu¬lated and experimental results reveal that the novel antenna performs well from 5.5 GHz to 7 GHz, and its monostatic RCS is reduced significantly from 5.8 GHz to 7 GHz. The agreement between measured and simulated data validates the present design

Aberrant posterior cingulate connectivity classify first-episode schizophrenia from controls: A machine learning study

Background Posterior cingulate cortex (PCC) is a key aspect of the default mode network (DMN). Aberrant PCC functional connectivity (FC) is implicated in schizophrenia, but the potential for PCC related changes as biological classifier of schizophrenia has not yet been evaluated. Methods We conducted a data-driven approach using resting-state functional MRI data to explore differences in PCC-based region- and voxel-wise FC patterns, to distinguish between patients with first-episode schizophrenia (FES) and demographically matched healthy controls (HC). Discriminative PCC FCs were selected via false discovery rate estimation. A gradient boosting classifier was trained and validated based on 100 FES vs. 93 HC. Subsequently, classification models were tested in an independent dataset of 87 FES patients and 80 HC using resting-state data acquired on a different MRI scanner. Results Patients with FES had reduced connectivity between PCC and frontal areas, left parahippocampal regions, left anterior cingulate cortex, and right inferior parietal lobule, but hyperconnectivity with left lateral temporal regions. Predictive voxel-wise clusters were similar to region-wise selected brain areas functionally connected with PCC in relation to discriminating FES from HC subject categories. Region-wise analysis of FCs yielded a relatively high predictive level for schizophrenia, with an average accuracy of 72.28% in the independent samples, while selected voxel-wise connectivity yielded an accuracy of 68.72%. Conclusion FES exhibited a pattern of both increased and decreased PCC-based connectivity, but was related to predominant hypoconnectivity between PCC and brain areas associated with DMN, that may be a useful differential feature revealing underpinnings of neuropathophysiology for schizophrenia

South Asian summer monsoon projections constrained by the Intedacadal Pacific Oscillation

A reliable projection of future South Asian summer monsoon (SASM) benefits a large population in Asia. Using a 100-member ensemble of simulations by the Max Planck Institute Earth System Model (MPI-ESM) and a 50-member ensemble of simulations by the Canadian Earth System Model (CanESM2), we find that internal variability can overshadow the forced SASM rainfall trend, leading to large projection uncertainties for the next 15 to 30 years. We further identify that the Interdecadal Pacific Oscillation (IPO) is, in part, responsible for the uncertainties. Removing the IPO-related rainfall variations reduces the uncertainties in the near-term projection of the SASM rainfall by 13 to 15% and 26 to 30% in the MPI-ESM and CanESM2 ensembles, respectively. Our results demonstrate that the uncertainties in near-term projections of the SASM rainfall can be reduced by improving prediction of near-future IPO and other internal modes of climate variabilit

Provenance analysis for instagram photos

As a feasible device fingerprint, sensor pattern noise (SPN) has been proven to be effective in the provenance analysis of digital images. However, with the rise of social media, millions of images are being uploaded to and shared through social media sites every day. An image downloaded from social networks may have gone through a series of unknown image manipulations. Consequently, the trustworthiness of SPN has been challenged in the provenance analysis of the images downloaded from social media platforms. In this paper, we intend to investigate the effects of the pre-defined Instagram images filters on the SPN-based image provenance analysis. We identify two groups of filters that affect the SPN in quite different ways, with Group I consisting of the filters that severely attenuate the SPN and Group II consisting of the filters that well preserve the SPN in the images. We further propose a CNN-based classifier to perform filter-oriented image categorization, aiming to exclude the images manipulated by the filters in Group I and thus improve the reliability of the SPN-based provenance analysis. The results on about 20, 000 images and 18 filters are very promising, with an accuracy higher than 96% in differentiating the filters in Group I and Group II