Secrecy outage analysis for Alamouti space-time block coded non-orthogonal multiple access

This letter proposed a novel transmission technique for physical layer security by applying the Alamouti Space-Time Block Coded Non-orthogonal Multiple Access (STBC-NOMA) scheme. The secure outage performance under both perfect successive interference cancellation (pSIC) and imperfect successive interference cancellation (ipSIC) are investigated. In particular, novel exact and asymptotic expressions of secrecy outage probability are derived. Numerical and theoretical results are presented to corroborate the derived expressions and to demonstrate the superiority of STBC-NOMA and its ability to enhance the secrecy outage performance compared to conventional NOMA

PointGPT: Auto-regressively Generative Pre-training from Point Clouds

Large language models (LLMs) based on the generative pre-training transformer (GPT) have demonstrated remarkable effectiveness across a diverse range of downstream tasks. Inspired by the advancements of the GPT, we present PointGPT, a novel approach that extends the concept of GPT to point clouds, addressing the challenges associated with disorder properties, low information density, and task gaps. Specifically, a point cloud auto-regressive generation task is proposed to pre-train transformer models. Our method partitions the input point cloud into multiple point patches and arranges them in an ordered sequence based on their spatial proximity. Then, an extractor-generator based transformer decoder, with a dual masking strategy, learns latent representations conditioned on the preceding point patches, aiming to predict the next one in an auto-regressive manner. Our scalable approach allows for learning high-capacity models that generalize well, achieving state-of-the-art performance on various downstream tasks. In particular, our approach achieves classification accuracies of 94.9% on the ModelNet40 dataset and 93.4% on the ScanObjectNN dataset, outperforming all other transformer models. Furthermore, our method also attains new state-of-the-art accuracies on all four few-shot learning benchmarks.Comment: 9 pages, 2 figure

Nonconservative behavior of dissolved molybdenum and its potential role in nitrogen cycling in the Bohai and Yellow Seas

Molybdenum plays an important role in marine biological activity, especially in nitrogen cycling as a cofactor for N2 fixation and nitrate reductase. However, the dissolved Mo (dMo) behavior and its interaction with N cycling in the coastal waters is still unclear. In this study, the dMo concentrations and parameters related to Mo distribution and N cycling in surface and bottom seawaters of the Bohai (BS) and Yellow Seas (YS) were examined. The results showed that dMo concentrations ranged from 36.4 nmol L-1 to 125.0 nmol L-1, most of which deviated significantly from the conservative line, indicating nonconservative behavior of Mo relative to salinity. The highest dMo concentrations occurring in 36°N section of north of the South YS (SYS), were close to conservative value (105 nmol L-1). Significant depletion up to 40-50 nmol L-1 of dMo mainly appeared in the BS, NYS and south of the SYS, suggesting the possible removal of dMo by biological utilization and particle adsorption. Particularly, the increasing dMo concentrations away the Yellow River estuary indicated that freshwater dilution was one of reasons for dMo distributions in the BS. The similar spatial distribution of dMo and dissolved Mn concentrations suggested the possible scavenging by MnOx phases for Mo removal. The negative correlation between dMo and chlorophyll-a (Chl-a) concentrations in surface seawaters suggested that biological uptake was involved in dMo removal. The depleted dMo in most of sites corresponded with the higher nitrite concentrations, implying the possible involvement of nitrate reduction process. Although the highest N2 fixation rates and relative abundances of cyanobacteria appeared in 36°N section, corresponding with the conservative dMo, suggesting that Mo may play a minor role in N2 fixation process there. The ten-folds of relative abundance of bacteria with nitrate reduction function than that with N2 fixation function suggested that dMo seems to play more important role in nitration reduction than nitrogen fixation in the BS and YS

Effects of hypoxia on serum hepatic chemistries of Tibet chicken and Shouguang chicken

Hypoxia is a major factor that affects the subsistence and development of multicellular organisms. Tibet chicken, as a unique native chicken breed in altiplano, shows genetic adaptation to hypoxia comparing with the breeds at the low altitude. In the present study, to explore effects of hypoxia on chicken fetal livers, eggs of Tibet chicken and Shouguang chicken were collected and the samples from each breed were divided into two groups, incubated in hypoxia and in normoxia respectively. The blood of embryos on the 16th day of incubation was collected and the serum chemistry  parameters indicating liver metabolism were determined, which included glutamic-pyruvic transaminase (GPT), aspartate aminotransferase (GOT), total bilirubin (TB), direct bilirubin (DB), total bile acid (TBA), gamma glutamyltransferase (GGT), alkaline phosphatease (ALP), lactate dehydrogenase (LDH), creatine kinase (CK), glucose and creatinine. The results show that biochemical indices varied significantly between hypoxia and normoxia except for GPT and glucose. Moreover, the concentration of ALP and LDH showed significant differences between the breeds and the incubations. The results suggest that the livers of both Shouguang chicken and Tibet chicken suffered damages in hypoxia, but the former was more serious. The results of this study support the opinion that Tibet chicken had better genetic adaptability on hypoxia, and made a good basis for further study of the genetic mechanism of adaptation to hypoxia.Key words: Hypoxia adaptation, liver metabolism, serum chemistry, Tibet chicken, chicken embryo

Fabrication Process Simulation of a PEM Fuel Cell Catalyst Layer and Its Microscopic Structure Characteristics

The catalyst layers (CLs) in proton exchange membrane fuel cells (PEMFCs) are porous composites of complex microstructures of the building blocks, i.e., Pt nano-particles, carbonaceous substrates and Nafion ionomers. It is important to understand the factors that control the microstructure formation in the fabrication process. A coarse-grained molecular dynamics (CG-MD) method is employed to investigate the fabrication process of CLs, which depends on the type and amount of components and also the type of the dispersion medium (ethylene glycol, isopropanol or hexanol) used during ink preparation of the catalyst-coated membranes (CCMs). The dynamical behaviors of all the components are outlined and analyzed following the fabrication steps. In addition, the Pt nano-particle size distribution is evaluated and compared with the labor testing. Furthermore, the primary pore size distributions in the final formations of three cases are shown and compared with the experiments. The sizes of the reconstructed agglomerates are also considered on the effect of solvent polarity. (C) 2012 The Electrochemical Society. [DOI: 10.1149/2.064203jes] All rights reserved

N-carbamylglutamate supplementation regulates hindgut microbiota composition and short-chain fatty acid contents in Charollais and Small Tail Han crossbred sheep

IntroductionThe objective of this study was to investigate the effects of N-carbamylglutamate (NCG) supplementation on the growth performance, hindgut microbiota composition, and short-chain fatty acid (SCFA) contents in Charollais and Small Tail Han crossbred sheep.MethodsA total of 16 female crossbred mutton sheep (Charollais × Small Tail Han), aged 4 months, with an initial body weight of 30.03 ± 0.08 kg, were utilized in a 60 days experiment. The sheep were divided into two groups based on their initial body weight. Each group consisted of 8 replicates, with each individual sheep considered as a replicate. The dietary treatments comprised a basal diet supplemented with either 0.00% or 0.12% NCG.Results and discussionOur findings indicate that NCG supplementation did not have a significant effect on the growth performance of mutton sheep. However, it did lead to changes in hindgut SCFA contents. Specifically, NCG supplementation increased the content of propanoic acid while decreasing acetic acid and hexanoic acid in the hindgut. Through microbiota analysis using the 16S rRNA technique, we identified Lachnospiraceae_NK3A20_group and Parasutterella as biomarkers for the hindgut microbiota in mutton sheep fed a diet containing NCG. Further analysis of the microbiota composition revealed that NCG supplementation significantly increased the abundance of Lachnospiraceae_NK3A20_group and Parasutterella, while decreasing unclassified_f_Lachnospiraceae and Lachnoclostridium. Correlation analysis between hindgut SCFA contents and microbiota composition revealed that the abundance of Lachnoclostridium was positively correlated with the contents of acetic acid and hexanoic acid, but negatively correlated with propanoic acid. Additionally, the abundance of Lachnospiraceae_NK3A20_group and Parasutterella was positively correlated with the content of propanoic acid, while being negatively correlated with acetic acid and hexanoic acid. Based on these findings, we conclude that dietary supplementation of 0.12% NCG can modulate hindgut SCFA contents in mutton sheep by regulating the composition of the hindgut microbiota

Security outage probability analysis of cognitive networks with multiple eavesdroppers for Industrial Internet of Things

The Industrial Internet of Things (IIoT) has been recognised as having the potential to benefit a range of industrial sectors substantially. However, widespread development and deployment of IIoT systems are limited for some reasons, the most significant of which are a shortage of spectrum resources and network security issues. Given the heterogeneity of IIoT devices, typical cryptographic security techniques are insufficient since they can suffer from challenges including computation, storage, latency, and interoperability. This paper presents a physical layer security analysis of the underlying cognitive radio networks for IIoT. Through consideration of the spectrum, IIoT devices can opportunistically utilise the primary spectrum, thereby improving spectrum efficiency and allowing access by an increased number of devices. Specifically, we propose two cognitive relay transmission (CRT) schemes, optimal single CRT (O-SCRT) and multiple CRT (MCRT), to improve transmission reliability further. Since it is challenging to obtain channel state information in the wiretap link, we provide a sub-optimal single CRT scheme and derive closed-form expressions of security outage probability by invoking both selection combination and maximal ratio combination techniques at the eavesdropper. To provide a benchmark, the round-robin single CRT scheme is also analysed. Simulation results are provided to verify our analysis and show that O-SCRT provides the best system security outage performance