Metasurface-based Modulation with Enhanced Interference Resilience

Reconfigurable Intelligent Surfaces (RISs) have great potential for Internet of Things (IoT) applications due to their cost-effectiveness and energy-efficiency. However, under the application of RIS, current RIS systems cannot actively predict and avoid interference, as evolving interference signals can dynamically change their frequency bands. To address this issue, we develop a learning-based dynamic RIS spectrum access scheme to avoid interference and enhance wireless transmission reliability. An intelligent metasurface-based modulation (MM) is designed for generating and reflecting anti-interference radio-frequency signals. Specifically, a Dyna-Q algorithm is employed at the RIS controller to learn the frequency of interference signals, which is used to determine the frequency of the carrier signals. Experiments are conducted on the proposed RIS demo system to evaluate its anti-interference capability, and the results show that our scheme leads to an increase of at least 50% in the system throughput. These numerical results demonstrate the effectiveness of proposed scheme

Doping dependence of phonon and quasiparticle heat transport of pure and Dy-doped Bi_2Sr_2CaCu_2O_{8+\delta} single crystals

The temperature and magnetic-field (H) dependences of thermal conductivity (\kappa) of Bi_2Sr_2CaCu_2O_{8+\delta} (Bi2212) are systematically measured for a broad doping range by using both pure Bi2212 single crystals with tuned oxygen contents and Bi_2Sr_2Ca_{1-x}Dy_xCu_2O_{8+\delta} (Dy-Bi2212) single crystals with different Dy contents x. In the underdoped samples, the quasiparticle (QP) peak below T_c is strongly suppressed, indicating strong QP scattering by impurities or oxygen defects, whereas the phonon conductivity is enhanced in moderately Dy-doped samples and a phonon peak at 10 K is observed for the first time in Bi2212 system, which means Dy^{3+} ions not only introduce the impurities or point defects but also stabilize the crystal lattice. The subkelvin data show that the QP heat conductivity gradually decreases upon lowering the hole doping level. The magnetic-field dependence of \kappa at temperature above 5 K is mainly due to the QP scattering off vortices. While the underdoped pure Bi2212 show very weak field dependence of \kappa, the Dy-doped samples present an additional "dip"-like term of \kappa(H) at low field, which is discussed to be related to the phonon scattering by free spins of Dy^{3+} ions. For non-superconducting Dy-Bi2212 samples with x \simeq 0.50, an interesting "plateau" feature shows up in the low-T \kappa(H) isotherms with characteristic field at 1 -- 2 T, for which we discuss the possible revlevance of magnon excitations.Comment: 11 pages, 11 figures, accepted for publication in Phys. Rev.

Interplay between unconventional superconductivity and heavy-fermion quantum criticality: CeCu2_2Si2_2 versus YbRh2_2Si2_2

In this paper the low-temperature properties of two isostructural canonical heavy-fermion compounds are contrasted with regards to the interplay between antiferromagnetic (AF) quantum criticality and superconductivity. For CeCu$_2$Si$_2$, fully-gapped d-wave superconductivity forms in the vicinity of an itinerant three-dimensional heavy-fermion spin-density-wave (SDW) quantum critical point (QCP). Inelastic neutron scattering results highlight that both quantum critical SDW fluctuations as well as Mott-type fluctuations of local magnetic moments contribute to the formation of Cooper pairs in CeCu$_2$Si$_2$. In YbRh$_2$Si$_2$, superconductivity appears to be suppressed at $T\gtrsim~10$ mK by AF order ($T_N$ = 70 mK). Ultra-low temperature measurements reveal a hybrid order between nuclear and 4f-electronic spins, which is dominated by the Yb-derived nuclear spins, to develop at $T_A$ slightly above 2 mK. The hybrid order turns out to strongly compete with the primary 4f-electronic order and to push the material towards its QCP. Apparently, this paves the way for heavy-fermion superconductivity to form at $T_c$ = 2 mK. Like the pressure - induced QCP in CeRhIn$_5$, the magnetic field - induced one in YbRh$_2$Si$_2$ is of the local Kondo-destroying variety which corresponds to a Mott-type transition at zero temperature. Therefore, these materials form the link between the large family of about fifty low-$T$ unconventional heavy - fermion superconductors and other families of unconventional superconductors with higher $T_c$s, notably the doped Mott insulators of the cuprates, organic charge-transfer salts and some of the Fe-based superconductors. Our study suggests that heavy-fermion superconductivity near an AF QCP is a robust phenomenon.Comment: 30 pages, 7 Figures, Accepted for publication in Philosophical Magazin

Exposure to famine in early life and the risk of obesity in adulthood in Qingdao : Evidence from the 1959-1961 Chinese famine

Background and aims: We aimed to evaluate the association between famine exposure during early life and obesity and obesity(max) (obese at the highest weight) in adulthood. Methods and results: Data were from two population-based cross-sectional surveys conducted in 2006 and 2009 in Qingdao, China. A total of 8185 subjects born between 1/1/1941 and 12/31/1971 were categorized into unexposed (born between 01/01/1962 and 12/31/1971), fetal/ infant exposed (born between 01/01/1959 and 12/31/1961), childhood exposed (born between 01/01/1949 and 12/31/1958) and adolescence exposed (born between 01/01/1941 and 12/31/1948) according to their age when exposed to the Chinese famine from 1959 to 1961. Obesity was defined as BMI (body mass index) >= 28.0 and obesitymax was defined as BMImax (BMI at the highest weight) >= 28.0. We compared fetal/ infant exposed, childhood exposed and adolescence exposed to the unexposed using logistic regression models to assess the effect of famine exposure on later obesity and obesitymax. Fetal/infant exposed (OR = 1.59, P <0.001), childhood exposed (OR = 1.42, P <0.01) and adolescence exposed (OR = 1.86, P <0.01) all had higher risks of obesity than the unexposed. Exposure groups were more likely to be obese at their highest weight than the unexposed, and ORs (95%CIs) for obesitymax in the fetal/ infant exposed, childhood exposed and adolescence exposed were 1.49(1.20e1.86), 1.24(1.02e1.49) and 1.64 (1.40 e1.93), respectively. Similar results were found in both men and women. Conclusion: Exposure to famine in early life was associated with increased risks of obesity and obesitymax in adulthood. Preventing undernutrition in early life appears beneficial to reduce the prevalence of later obesity. (C) 2016 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.Peer reviewe

C-Reactive Protein and Gamma-Glutamyltransferase Concentrations in Relation to the Prevalence of Type 2 Diabetes Diagnosed by Glucose or HbA1c Criteria in Chinese Adults in Qingdao, China

Aims. To investigate the association of C-reactive protein (CRP) and gamma glutamyltransferase (GGT) concentrations with newly diagnosed diabetes defined by either glucose or HbA1c criteria in Chinese adults. Methods. A population-based cross-sectional study was conducted in 2006. Data from 1167 men and 1607 women aged 35–74 years were analyzed. Diabetes was defined according to either glucose or HbA1c criteria alone. Results. Compared with nondiabetes, multivariate-adjusted OR (95%CI) was 1.13 (0.90,1.42) in men and 1.21 (1.00,1.45) in women for CRP and 1.42 (1.18,1.72) and 1.57 (1.31,1.87) for GGT, respectively. Neither CRP nor GGT was associated with the presence of diabetes defined by the HbA1c criterion. Conclusions. The effect of elevated CRP on diabetes defined by the glucose criterion was mediated through obesity, but elevated GGT was an independent risk factor for diabetes in this Chinese population. None of the two was, however, associated with the elevated HbA1c concentrations

Fast and Accurate Lung Tumor Spotting and Segmentation for Boundary Delineation on CT Slices In A Coarse-To-Fine Framework

Label noise and class imbalance are two of the critical challenges when training image-based deep neural networks, especially in the biomedical image processing domain. Our work focuses on how to address the two challenges effectively and accurately in the task of lesion segmentation from biomedical/medical images. To address the pixel-level label noise problem, we propose an advanced transfer training and learning approach with a detailed DICOM pre-processing method. To address the tumor/non-tumor class imbalance problem, we exploit a self-adaptive fully convolutional neural network with an automated weight distribution mechanism to spot the Radiomics lung tumor regions accurately. Furthermore, an improved conditional random field method is employed to obtain sophisticated lung tumor contour delineation and segmentation. Finally, our approach has been evaluated using several well-known evaluation metrics on the Lung Tumor segmentation dataset used in the 2018 IEEE VIP-CUP Challenge. Experimental results show that our weakly supervised learning algorithm outperforms other deep models and state-of-the-art approache

Mathematical modelling and experimental investigation of dehumidifier drying of radiata pine timber

A dynamic kiln-wide wood drying model was developed previously to solve the integral form of the unsteady-state mass, momentum and energy balance equations in the air side. For the wood side, an empirical model, characteristic drying curve, for the internal moisture movement is used, which was obtained for low and medium temperature drying of Pinus radiata, with a medium velocity of 1.4- 4.1 m s–1. As part of the research programme to improve the design and control of dehumidifier wood drying kilns, the wood drying model has been assessed using the experimental data measured under drying conditions similar to those in dehumidifier kiln. It is noted that close agreement between the modelled results and the experimental data can be obtained for Pinus radiata drying processes with a medium air velocity (&lt; 5 m s–1). However, larger discrepancy between the modelled results and the measured data has been observed with a higher velocity (8 m s–1). To solve this problem a new characteristic drying curve, based on a two-zone diffusion model, has been used in the kiln-wide wood drying model and more accurate results have been obtained