The qq-log-convexity of Domb's polynomials

In this paper, we prove the $q$-log-convexity of Domb's polynomials, which was conjectured by Sun in the study of Ramanujan-Sato type series for powers of $\pi$. As a result, we obtain the log-convexity of Domb's numbers. Our proof is based on the $q$-log-convexity of Narayana polynomials of type $B$ and a criterion for determining $q$-log-convexity of self-reciprocal polynomials.Comment: arXiv admin note: substantial text overlap with arXiv:1308.273

On the qq-log-convexity conjecture of Sun

In his study of Ramanujan-Sato type series for $1/\pi$, Sun introduced a sequence of polynomials $S_n(q)$ as given by $$S_n(q)=\sum\limits_{k=0}^n{n\choose k}{2k\choose k}{2(n-k)\choose n-k}q^k,$$ and he conjectured that the polynomials $S_n(q)$ are $q$-log-convex. By imitating a result of Liu and Wang on generating new $q$-log-convex sequences of polynomials from old ones, we obtain a sufficient condition for determining the $q$-log-convexity of self-reciprocal polynomials. Based on this criterion, we then give an affirmative answer to Sun's conjecture

Temperature dependence of electron-spin relaxation in a single InAs quantum dot at zero applied magnetic field

The temperature-dependent electron spin relaxation of positively charged excitons in a single InAs quantum dot (QD) was measured by time-resolved photoluminescence spectroscopy at zero applied magnetic fields. The experimental results show that the electron-spin relaxation is clearly divided into two different temperature regimes: (i) T < 50 K, spin relaxation depends on the dynamical nuclear spin polarization (DNSP) and is approximately temperature-independent, as predicted by Merkulov et al. (ii) T > about 50 K, spin relaxation speeds up with increasing temperature. A model of two LO phonon scattering process coupled with hyperfine interaction is proposed to account for the accelerated electron spin relaxation at higher temperatures.Comment: 10 pages, 4 figure

PnP-AdaNet: Plug-and-Play Adversarial Domain Adaptation Network with a Benchmark at Cross-modality Cardiac Segmentation

Deep convolutional networks have demonstrated the state-of-the-art performance on various medical image computing tasks. Leveraging images from different modalities for the same analysis task holds clinical benefits. However, the generalization capability of deep models on test data with different distributions remain as a major challenge. In this paper, we propose the PnPAdaNet (plug-and-play adversarial domain adaptation network) for adapting segmentation networks between different modalities of medical images, e.g., MRI and CT. We propose to tackle the significant domain shift by aligning the feature spaces of source and target domains in an unsupervised manner. Specifically, a domain adaptation module flexibly replaces the early encoder layers of the source network, and the higher layers are shared between domains. With adversarial learning, we build two discriminators whose inputs are respectively multi-level features and predicted segmentation masks. We have validated our domain adaptation method on cardiac structure segmentation in unpaired MRI and CT. The experimental results with comprehensive ablation studies demonstrate the excellent efficacy of our proposed PnP-AdaNet. Moreover, we introduce a novel benchmark on the cardiac dataset for the task of unsupervised cross-modality domain adaptation. We will make our code and database publicly available, aiming to promote future studies on this challenging yet important research topic in medical imaging

Enhancement of Transition Temperature in FexSe0.5Te0.5 Film via Iron Vacancies

The effects of iron deficiency in FexSe0.5Te0.5 thin films (0.8<x<1) on superconductivity and electronic properties have been studied. A significant enhancement of the superconducting transition temperature (TC) up to 21K was observed in the most Fe deficient film (x=0.8). Based on the observed and simulated structural variation results, there is a high possibility that Fe vacancies can be formed in the FexSe0.5Te0.5 films. The enhancement of TC shows a strong relationship with the lattice strain effect induced by Fe vacancies. Importantly, the presence of Fe vacancies alters the charge carrier population by introducing electron charge carriers, with the Fe deficient film showing more metallic behavior than the defect-free film. Our study provides a means to enhance the superconductivity and tune the charge carriers via Fe vacancy, with no reliance on chemical doping.Comment: 15 pages, 4 figure

Nested Tail-Biting Convolutional Codes Construction for Short Packet Communications

Tail-biting convolutional codes (TBCCs) have become a research hotspot in the short-block-length regime due to the growing interest in strong short packet com-munications with low latency and ultra-reliability. TBCCs can maintain the decoding performance without rate loss caused by the tailed bits in the traditional convolutional encoder, which also have good rate compatibility with bet¬ter decoding performance than those of the iterative scheme for short block length codes. In this paper, a search algorithm is proposed to construct a set of rate-compatible TBCCs (RC-TBCCs) with consistent good frame error rate (FER) performance for fixed information length at various code rates. The algorithm considers the minimum distance profile of TBCCs. A set of RC-TBCCs is constructed for code rates from 1/3 to 1/8. The simulation results show that the proposed RC-TBCCs are superior to the LTE standard RC-TBCCs at different code rates

Carbon Storage and Sequestration Under Different Stocking Rates in a Eurasian Desert Steppe in China

The research on carbon source/sink of terrestrial ecosystem is an important part of global climate change. Under the sustainable grazing management, the carbon storage in grassland ecosystem will increase, which promotes the carbon sequestration in the grassland area. In order to understand the carbon sequestration in grazing system of desert steppe, a sheep grazing experiment for completely random block design was conducted in desert steppe. There were 4 stocking rates and 3 replications in this experiment. The effects of annual precipitation and stocking rate on the carbon sequestration of desert steppe were compared. The stocking rate treatments were as follows: no grazing, light grazing, moderate grazing, and heavy grazing. Plant composition, biomass, individual plant carbon, soil carbon, emission of soil and livestock, and carbon flux of ecosystem were measured. We discussed carbon storage and carbon sequestration based on the above indicators. The results showed that stocking rate has different effects on the aboveground net primary production, belowground net primary production, carbon storage of grassland ecosystem, net ecosystem exchange and soil respiration. We further analyzed the impact factors of different variables, understood the carbon sequestration and transition process from plant to soil in this steppe. Finally, we concluded that the optimal stocking rate in desert steppe according to the vegetation, balance of soil nutrients and livestock performance, provides the theoretical reference for the sustainable grassland management based on grassland carbon sequestration