Linear Framework of RIS-Assisted Downlink Communication System

Reconfigurable intelligent surfaces (RIS) has emerged as a promising approach for efficiently enhancing communication performance via passive signal reflection. However, in high-mobility scenarios like vehicular communications, the rapidly changing channel presents challenges in acquiring instantaneous channel state information (CSI) for RIS systems with many reflectors, impacting transmission reliability. To overcome this issue, we present an innovative equivalent linear framework equipped with a low-complexity transmitter signal waveform design and receiver signal detection method for downlink communication systems, substantially enhancing stability in fast fading environments. Simulation results indicate that the proposed designs achieve higher communication reliability with low complexity, significantly improving performance in high-mobility scenarios

An Instrument for In Situ Measuring the Volume Scattering Function of Water: Design, Calibration and Primary Experiments

The optical volume scattering function (VSF) of seawater is a fundamental property used in the calculation of radiative transfer for applications in the study of the upper-ocean heat balance, the photosynthetic productivity of the ocean, and the chemical transformation of photoreactive compounds. A new instrument to simultaneously measure the VSF in seven directions between 20° to 160°, the attenuation coefficient, and the depth of water is presented. The instrument is self-contained and can be automatically controlled by the depth under water. The self-contained data can be easily downloaded by an ultra-short-wave communication system. A calibration test was performed in the laboratory based on precise estimation of the scattering volume and optical radiometric calibration of the detectors. The measurement error of the VSF measurement instrument has been estimated in the laboratory based on the Mie theory, and the average error is less than 12%. The instrument was used to measure and analyze the variation characteristics of the VSF with angle, depth and water quality in Daya Bay for the first time. From these in situ data, we have found that the phase functions proposed by Fournier-Forand, measured by Petzold in San Diego Harbor and Sokolov in Black Sea do not fit with our measurements in Daya. These discrepancies could manly due to high proportion of suspended calcium carbonate mineral-like particles with high refractive index in Daya Bay

Weakly Supervised Patch Label Inference Networks for Efficient Pavement Distress Detection and Recognition in the Wild

Automatic image-based pavement distress detection and recognition are vital for pavement maintenance and management. However, existing deep learning-based methods largely omit the specific characteristics of pavement images, such as high image resolution and low distress area ratio, and are not end-to-end trainable. In this paper, we present a series of simple yet effective end-to-end deep learning approaches named Weakly Supervised Patch Label Inference Networks (WSPLIN) for efficiently addressing these tasks under various application settings. To fully exploit the resolution and scale information, WSPLIN first divides the pavement image under different scales into patches with different collection strategies and then employs a Patch Label Inference Network (PLIN) to infer the labels of these patches. Notably, we design a patch label sparsity constraint based on the prior knowledge of distress distribution, and leverage the Comprehensive Decision Network (CDN) to guide the training of PLIN in a weakly supervised way. Therefore, the patch labels produced by PLIN provide interpretable intermediate information, such as the rough location and the type of distress. We evaluate our method on a large-scale bituminous pavement distress dataset named CQU-BPDD. Extensive results demonstrate the superiority of our method over baselines in both performance and efficiency.Comment: Extension of ICASSP 2021 Paper entitled "Weakly Supervised Patch Label Inference Network with Image Pyramid for Pavement Diseases Recognition in the Wild", Submitted to IEEE T-IT

Surface phases of the transition-metal dichalcogenide IrT e2

Transition-metal dichalcogenide IrTe2 has attracted attention because of its striped lattice, charge ordering, and superconductivity. We have investigated the surface structure of IrTe2, using low-energy electron diffraction and scanning tunneling microscopy. A complex striped lattice modulation as a function of temperature is observed, which shows hysteresis between cooling and warming. While the bulk 5 × 1 and 8 × 1 phases appear at high temperatures, the surface ground state has the 6 × 1 phase, not seen in the bulk, and the surface transition temperatures are distinct from the bulk. The broken symmetry at the surface creates a quite different phase diagram, with the coexistence of several periodicities resembling devil\u27s staircase behavior

Turn-Based War Chess Model and Its Search Algorithm per Turn

War chess gaming has so far received insufficient attention but is a significant component of turn-based strategy games (TBS) and is studied in this paper. First, a common game model is proposed through various existing war chess types. Based on the model, we propose a theory frame involving combinational optimization on the one hand and game tree search on the other hand. We also discuss a key problem, namely, that the number of the branching factors of each turn in the game tree is huge. Then, we propose two algorithms for searching in one turn to solve the problem: (1) enumeration by order; (2) enumeration by recursion. The main difference between these two is the permutation method used: the former uses the dictionary sequence method, while the latter uses the recursive permutation method. Finally, we prove that both of these algorithms are optimal, and we analyze the difference between their efficiencies. An important factor is the total time taken for the unit to expand until it achieves its reachable position. The factor, which is the total number of expansions that each unit makes in its reachable position, is set. The conclusion proposed is in terms of this factor: Enumeration by recursion is better than enumeration by order in all situations

A Dielectric Metasurface Optical Chip for the Generation of Cold Atoms

Compact and robust cold atom sources are increasingly important for quantum research, especially for transferring cutting-edge quantum science into practical applications. In this letter, we report on a novel scheme that utilizes a metasurface optical chip to replace the conventional bulky optical elements used to produce a cold atomic ensemble with a single incident laser beam, which is split by the metasurface into multiple beams of the desired polarization states. Atom numbers $~10^7$ and temperatures (about 35 ${\mu}$K) of relevance to quantum sensing are achieved in a compact and robust fashion. Our work highlights the substantial progress towards fully integrated cold atom quantum devices by exploiting metasurface optical chips, which may have great potential in quantum sensing, quantum computing and other areas

Causal relationship between the gut microbiota, immune cells, and coronary heart disease: a mediated Mendelian randomization analysis

BackgroundRecent studies have shown that the gut microbiota (GM), immune cells, and coronary heart disease (CHD) are closely related, but the causal nature of these relationships is largely unknown. This study aimed to investigate this causal relationship and reveal the effect of GM and immune cells on the risk of developing CHD using mediated Mendelian randomization (MR) analysis.MethodsFirst, we searched for data related to GM, immune cells, and CHD through published genome-wide association studies (GWAS). We filtered the single nucleotide polymorphisms (SNPs) associated with GM and immune cells and then performed the first MR analysis to identify disease-associated intestinal bacteria and disease-associated immune cells. Subsequently, three MR analyses were conducted: from disease-associated GM to disease-associated immune cells, from disease-associated immune cells to CHD, and from disease-associated GM to CHD. Each MR analysis was conducted using inverse variance weighting (IVW), MR-Egger regression, weighted median, weighted models, and simple models.ResultsA total of six GM and 25 immune cells were found to be associated with CHD. In the MR analysis using the inverse variance weighting (IVW) method, g__Desulfovibrio.s__Desulfovibrio_piger was associated with EM DN (CD4–CD8–) %T cells (P < 0.05 and OR > 1), EM DN (CD4–CD8–) %T cells was associated with CHD (P < 0.05 and OR < 1), and g__Desulfovibrio.s__Desulfovibrio_piger was associated with CHD (P < 0.05 and OR < 1).ConclusionAn increase in the abundance of g__Desulfovibrio.s__Desulfovibrio_piger leads to an increase in the amount of EM DN (CD4–CD8–) %T cells, and an increase in the amount of EM DN (CD4–CD8–) %T cells reduces the risk of developing CHD. Our study provides some references for reducing the incidence of CHD by regulating GM and immune cells

Single-pixel computational ghost imaging with helicity-dependent metasurface hologram

A helicity-dependent computational ghost image generated by a metasurface hologram offers a promising optical encryption scheme.</jats:p

Metabolomic analysis of rumen-protected branched-chain amino acids in primiparous dairy cows

IntroductionPeripartal cows are susceptible to a negative energy balance due to inadequate nutrient intake and high energy requirements for lactation. Improving the energy metabolism of perinatal dairy cows is crucial in increasing production in dairy cows.MethodsIn this study, we investigated the impact of rumen-protected branched-chain amino acid (RPBCAA) on the production performance, energy and lipid metabolism, oxidative stress, and immune function of primiparous dairy cows using metabolomics through a single-factor experiment. Twenty healthy primiparous Holstein cows were selected based on body condition scores and expected calving date, and were randomly divided into RPBCAA (n = 10) and control (n = 10) groups. The control group received a basal diet from calving until 21 d in milk, and the RPBCAA group received the basal diet and 44.6 g/d RPLeu, 25.14 g/d RPIle, and 25.43 g/d RPVal.ResultsIn comparison to the control group, the supplementation of RPBCAA had no significant effect on milk yield and milk composition of the dairy cows. Supplementation with RPBCAA significantly increased the concentrations of insulin, insulin growth factor 1, glucagon, and growth hormones, which are indicators of energy metabolism in postpartum cows. The very low density lipoprotein, fatty acid synthase, acetyl coenzyme A carboxylase, and hormone-sensitive lipase contents of the RPBCAA group were significantly greater than that of the control group; these metrics are related to lipid metabolism. In addition, RPBCAA supplementation significantly increased serum glutathione peroxidase and immunoglobulin G concentrations and decreased malondialdehyde concentrations. Liquid chromatography–mass spectrometry (LC-MS) analysis revealed 414 serum and 430 milk metabolic features. Supplementation with RPBCAA primarily increased concentrations of amino acid and lipid metabolism pathways and upregulated the abundance of serotonin, glutamine, and phosphatidylcholines.DiscussionIn summary, adding RPBCAA to the daily ration can influence endocrine function and improve energy metabolism, regulate amino acid and lipid metabolism, mitigate oxidative stress and maintain immune function on primiparous cows in early lactation