An Adaptive Self-Interference Cancelation/Utilization and ICA-Assisted Semi-Blind Full-Duplex Relay System for LLHR IoT

In this article, we propose a semi-blind full-duplex (FD) amplify-and-forward (AF) relay system with adaptive self-interference (SI) processing assisted by independent component analysis (ICA) for low-latency and high-reliability (LLHR) Internet of Things (IoT). The SI at FD relay is not necessarily canceled as much as possible like the conventional approaches, but is canceled or utilized based on a signal-to-residual-SI ratio (SRSIR) threshold at relay. According to the selected SI processing mode at relay, an ICA-based adaptive semi-blind scheme is proposed for signal separation and detection at destination. The proposed FD relay system not only features reduced signal processing cost of SI cancelation but also achieves a much higher degree of freedom in signal detection. The resulting bit error rate (BER) performance is robust against a wide range of SRSIR, much better than that of conventional FD systems, and close to the ideal case with perfect channel state information (CSI) and perfect SI cancelation. The proposed system also requires negligible spectral overhead as only a nonredundant precoding is needed for ambiguity elimination in ICA. In addition, the proposed system enables full resource utilization with consecutive data transmission at all time and same frequency, leading to much higher throughput and energy efficiency than the time-splitting and power-splitting-based self-energy recycling approaches that utilize only partial resources. Furthermore, an intensive analysis is provided, where the SRSIR thresholds for the adaptive SI processing mode selection and the BER expressions with ICA incurred ambiguities are derived

Law Article-Enhanced Legal Case Matching: a Causal Learning Approach

Legal case matching, which automatically constructs a model to estimate the similarities between the source and target cases, has played an essential role in intelligent legal systems. Semantic text matching models have been applied to the task where the source and target legal cases are considered as long-form text documents. These general-purpose matching models make the predictions solely based on the texts in the legal cases, overlooking the essential role of the law articles in legal case matching. In the real world, the matching results (e.g., relevance labels) are dramatically affected by the law articles because the contents and the judgments of a legal case are radically formed on the basis of law. From the causal sense, a matching decision is affected by the mediation effect from the cited law articles by the legal cases, and the direct effect of the key circumstances (e.g., detailed fact descriptions) in the legal cases. In light of the observation, this paper proposes a model-agnostic causal learning framework called Law-Match, under which the legal case matching models are learned by respecting the corresponding law articles. Given a pair of legal cases and the related law articles, Law-Match considers the embeddings of the law articles as instrumental variables (IVs), and the embeddings of legal cases as treatments. Using IV regression, the treatments can be decomposed into law-related and law-unrelated parts, respectively reflecting the mediation and direct effects. These two parts are then combined with different weights to collectively support the final matching prediction. We show that the framework is model-agnostic, and a number of legal case matching models can be applied as the underlying models. Comprehensive experiments show that Law-Match can outperform state-of-the-art baselines on three public datasets.Comment: 10 pages accepted by SIGIR202

Full-Duplex Versus Half-Duplex Amplify-and-Forward Relaying: Which is More Energy Efficient in 60-GHz Dual-Hop Indoor Wireless Systems?

We provide a comprehensive energy efficiency (EE) analysis of the full-duplex (FD) and half-duplex (HD) amplify-and-forward (AF) relay-assisted 60-GHz dual-hop indoor wireless systems, aiming to answer the question of which relaying mode is greener (more energy efficient) and to address the issue of EE optimization. We develop an opportunistic relaying mode selection scheme, where FD relaying with one-stage self-interference cancellation (passive suppression) or two-stage self-interference cancellation (passive suppression + analog cancellation) or HD relaying is opportunistically selected, together with transmission power adaptation, to maximize the EE with given channel gains. A low-complexity joint mode selection and EE optimization algorithm are proposed. We show a counter-intuitive finding that with a relatively loose maximum transmission power constraint, FD relaying with two-stage self-interference cancellation is preferable to both FD relaying with one-stage self-interference cancellation and HD relaying, resulting in a higher optimized EE. A full range of power consumption sources is considered to rationalize our analysis. The effects of imperfect self-interference cancellation at relay, drain efficiency, and static circuit power on EE are investigated. Simulation results verify our theoretical analysis

Continental interior and edge breakup at convergent margins induced by subduction direction reversal: a numerical modeling study applied to the South China Sea margin

Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Tectonics 39(11), (2020): e2020TC006409, doi:10.1029/2020TC006409.The dynamics of continental breakup at convergent margins has been described as the results of backarc opening caused by slab rollback or drag force induced by subduction direction reversal. Although the rollback hypothesis has been intensively studied, our understanding of the consequence of subduction direction reversal remains limited. Using thermo‐mechanical modeling based on constraints from the South China Sea (SCS) region, we investigate how subduction direction reversal controls the breakup of convergent margins. The numerical results show that two distinct breakup modes, namely, continental interior and edge breakup (“edge” refers to continent above the plate boundary interface), may develop depending on the “maturity” of the convergent margin and the age of the oceanic lithosphere. For a slab age of ~15 to ~45 Ma, increasing the duration of subduction promotes the continental interior breakup mode, where a large block of the continental material is separated from the overriding plate. In contrast, the continental edge breakup mode develops when the subduction is a short‐duration event, and in this mode, a wide zone of less continuous continental fragments and tearing of the subducted slab occur. These two modes are consistent with the interior (relic late Mesozoic arc) and edge (relic forearc) rifting characteristics in the western and eastern SCS margin, suggesting that variation in the northwest‐directed subduction duration of the Proto‐SCS might be a reason for the differential breakup locus along the strike of the SCS margin. Besides, a two‐segment trench associated with the northwest‐directed subduction is implied in the present‐day SCS region.This research was supported by the Guangdong NSF research team project (2017A030312002), the Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0205), the K. C. Wong Education Foundation (GJTD‐2018‐13), the Strategic Priority Research Program of the Chinese Academy of Science (XDA13010303), the Chinese Academy of Sciences (Y4SL021001, QYZDY‐SSWDQC005, 133244KYSB20180029, and ISEE2019ZR01), the NSFC project (41606073, 41890813, and 41576070), the IODP‐China Foundation, the OMG Visiting Fellowship (OMG18‐15), and the Hong Kong Research Grant Council Grants (Nos. 14313816 and 14304820).2021-04-0

RNA-Seq Analyses of Midgut and Fat Body Tissues Reveal the Molecular Mechanism Underlying Spodoptera litura Resistance to Tomatine

Plants produce secondary metabolites to provide chemical defense against herbivorous insects, whereas insects can induce the expression of detoxification metabolism-related unigenes in counter defense to plant xenobiotics. Tomatine is an important secondary metabolite in tomato (Lycopersicon esculentum L.) that can protect the plant from bacteria and insects. However, the mechanism underlying the adaptation of Spodoptera litura, a major tomato pest, to tomatine in tomato is largely unclear. In this study, we first found that the levels of tomatine in tomatoes subjected to S. litura treatment were significantly increased. Second, we confirmed the inhibitory effect of tomatine on S. litura by adding moderate amounts of commercial tomatine to an artificial diet. Then, we utilized RNA-Seq to compare the differentially expressed genes (DEGs) in the midgut and fat body tissues of S. litura exposed to an artificial diet supplemented with tomatine. In total, upon exposure to tomatine, 134 and 666 genes were upregulated in the S. litura midgut and fat body, respectively. These DEGs comprise a significant number of detoxification-related genes, including 7 P450 family genes, 8 glutathione S-transferases (GSTs) genes, 6 ABC transport enzyme genes, 9 UDP-glucosyltransferases genes and 3 carboxylesterases genes. Moreover, KEGG analysis demonstrated that the upregulated genes were enriched in xenobiotic metabolism by cytochrome P450s, ABC transporters and drug metabolism by other enzymes. Furthermore, as numerous GSTs were induced by tomatine in S. litura, we chose one gene, namely GSTS1, to confirm the detoxification function on tomatine. Expression profiling revealed that GSTS1 transcripts were mainly expressed in larvae, and the levels were the highest in the midgut. Finally, when larvae were injected with double-stranded RNA specific to GSTS1, the transcript levels in the midgut and fat body decreased, and the negative effect of the plant xenobiotic tomatine on larval growth was magnified. These results preliminarily clarified the molecular mechanism underlying the resistance of S. litura to tomatine, establishing a foundation for subsequent pest control

Fork head transcription factor is required for ovarian mature in the brown planthopper, Nilaparvata lugens (Stål)

<p>Abstract</p> <p>Background</p> <p>The brown planthopper (BPH), <it>Nilaparvata lugens</it>, is the most devastating rice pest in many areas throughout Asia. The reproductive system of female <it>N. lugens </it>consists of a pair of ovaries with 24-33 ovarioles per ovary in most individuals which determine its fecundity. The fork head (Fox) is a transcriptional regulatory molecule, which regulates and controls many physiological processes in eukaryotes. The Fox family has several subclasses and members, and several Fox factors have been reported to be involved in regulating fecundity.</p> <p>Results</p> <p>We have cloned a fork head gene in <it>N. lugens</it>. The full-length cDNA of <it>Nl</it>FoxA is 1789 bp and has an open reading frame of 1143 bp, encoding a protein of 380 amino acids. Quantitative real-time PCR (RT-qPCR) and Reverse Transcription- PCR (RT-PCR) analysis revealed that <it>NlFoxA </it>mRNA was mainly expressed in the fat body, midgut, cuticle and Malpighian tube, and was expressed continuously with little change during all the developmental stages. <it>Nl</it>FoxA belongs to the FoxA subfamily of the Fox transcription factors. Knockdown of <it>NlFoxA </it>expression by RNAi using artificial diet containing double-stranded RNA (dsRNA) significantly decreased the number of offspring and impacted the development of ovaries. ELISA and Western blot analyses showed that feeding-based RNAi of <it>NlFoxA </it>gene also resulted in decreased expression of vitellogenin (Vg) protein.</p> <p>Conclusion</p> <p><it>Nl</it>FoxA plays an important role in regulation of fecundity and development of ovaries in the BPH via regulating vitellogenin expression.</p

Generative Retrieval with Semantic Tree-Structured Item Identifiers via Contrastive Learning

The retrieval phase is a vital component in recommendation systems, requiring the model to be effective and efficient. Recently, generative retrieval has become an emerging paradigm for document retrieval, showing notable performance. These methods enjoy merits like being end-to-end differentiable, suggesting their viability in recommendation. However, these methods fall short in efficiency and effectiveness for large-scale recommendations. To obtain efficiency and effectiveness, this paper introduces a generative retrieval framework, namely SEATER, which learns SEmAntic Tree-structured item identifiERs via contrastive learning. Specifically, we employ an encoder-decoder model to extract user interests from historical behaviors and retrieve candidates via tree-structured item identifiers. SEATER devises a balanced k-ary tree structure of item identifiers, allocating semantic space to each token individually. This strategy maintains semantic consistency within the same level, while distinct levels correlate to varying semantic granularities. This structure also maintains consistent and fast inference speed for all items. Considering the tree structure, SEATER learns identifier tokens' semantics, hierarchical relationships, and inter-token dependencies. To achieve this, we incorporate two contrastive learning tasks with the generation task to optimize both the model and identifiers. The infoNCE loss aligns the token embeddings based on their hierarchical positions. The triplet loss ranks similar identifiers in desired orders. In this way, SEATER achieves both efficiency and effectiveness. Extensive experiments on three public datasets and an industrial dataset have demonstrated that SEATER outperforms state-of-the-art models significantly.Comment: 8 main pages, 3 pages for appendi

Energy-Efficient Full-Duplex Cooperative Nonorthogonal Multiple Access

The full-duplex (FD) cooperative nonorthogonal multiple access (NOMA) achieves a superior throughput over the conventional half-duplex (HD) cooperative NOMA, wherein the strong users (SUs) with good channel conditions can act as an FD relay node for the weak users with poor channel conditions. However, the energy efficiency (EE) of a cooperative NOMA may be degraded due to the additional power consumption incurred at the SUs. We are, therefore, motivated to investigate the EE maximization problem of an FD cooperative NOMA system. More importantly, we investigate the 'signal-to-inference-noise ratio gap reversal' problem of cooperative NOMA systems, which imposes successive interference cancellation (SIC) performance degradation at the SUs. This problem has not been documented in the existing cooperative NOMA literature. A low-complexity algorithm is proposed for maximizing the system's EE while guaranteeing a successful SIC operation. Our numerical results show that the proposed algorithm achieves both a higher EE and throughput over the existing HD cooperative NOMA and nonadaptive FD cooperative NOMA. More importantly, the proposed scheme guarantees a successful SIC operation at the SUs

Deficiency in Silicon Transporter Lsi1 Compromises Inducibility of Anti-herbivore Defense in Rice Plants

Silicon (Si) application can significantly enhance rice resistance against herbivorous insects. However, the underlying mechanism is elusive. In this study, silicon transporter mutant OsLsi1 and corresponding wild-type rice (WT) were treated with and without Si to determine Si effects on rice resistance to leaffolder (LF), Cnaphalocrocis medinalis (Guenée) (Lepidoptera: Pyralidae). Si application on WT plants significantly promoted rice plant growth, upregulated expression level of OsLsi1 and increased Si accumulation in the leaves and roots, as well as effectively reduced LF weight gain, while it showed only marginal or no effect on the mutant plants. Furthermore, upon LF infestation, transcript levels of OsLOX, OsAOS2, OsCOI1a, OsCOI1b, and OsBBPI, and activity of catalase, superoxide dismutase, peroxidase, and polyphenol oxidase were significantly higher in Si-treated than untreated WT plants. However, OsLsi1 mutant plants displayed higher susceptibility to LF, and minimal response of defense-related enzymes and jasmonate dependent genes to Si application. These results suggest that induced defense plays a vital role in Si-enhanced resistance and deficiency in silicon transporter Lsi1 compromises inducibility of anti-herbivore defense in rice plants