Time-Hopping Multiple-Access for Backscatter Interference Networks

Future Internet-of-Things (IoT) is expected to wirelessly connect tens of billions of low-complexity devices. Extending the finite battery life of massive number of IoT devices is a crucial challenge. The ultra-low-power backscatter communications (BackCom) with the inherent feature of RF energy harvesting is a promising technology for tackling this challenge. Moreover, many future IoT applications will require the deployment of dense IoT devices, which induces strong interference for wireless information transfer (IT). To tackle these challenges, in this paper, we propose the design of a novel multiple-access scheme based on time-hopping spread-spectrum (TH-SS) to simultaneously suppress interference and enable both two-way wireless IT and one-way wireless energy transfer (ET) in coexisting backscatter reader-tag links. The performance analysis of the BackCom network is presented, including the bit-error rates for forward and backward IT and the expected energytransfer rate for forward ET, which account for non-coherent and coherent detection at tags and readers, and energy harvesting at tags, respectively. Our analysis demonstrates a tradeoff between energy harvesting and interference performance. Thus, system parameters need to be chosen carefully to satisfy given BackCom system performance requirement.ARC Discovery Projects Grant DP14010113

Integrating Sensing, Communication, and Power Transfer: Multiuser Beamforming Design

In the sixth-generation (6G) networks, massive low-power devices are expected to sense environment and deliver tremendous data. To enhance the radio resource efficiency, the integrated sensing and communication (ISAC) technique exploits the sensing and communication functionalities of signals, while the simultaneous wireless information and power transfer (SWIPT) techniques utilizes the same signals as the carriers for both information and power delivery. The further combination of ISAC and SWIPT leads to the advanced technology namely integrated sensing, communication, and power transfer (ISCPT). In this paper, a multi-user multiple-input multiple-output (MIMO) ISCPT system is considered, where a base station equipped with multiple antennas transmits messages to multiple information receivers (IRs), transfers power to multiple energy receivers (ERs), and senses a target simultaneously. The sensing target can be regarded as a point or an extended surface. When the locations of IRs and ERs are separated, the MIMO beamforming designs are optimized to improve the sensing performance while meeting the communication and power transfer requirements. The resultant non-convex optimization problems are solved based on a series of techniques including Schur complement transformation and rank reduction. Moreover, when the IRs and ERs are co-located, the power splitting factors are jointly optimized together with the beamformers to balance the performance of communication and power transfer. To better understand the performance of ISCPT, the target positioning problem is further investigated. Simulations are conducted to verify the effectiveness of our proposed designs, which also reveal a performance tradeoff among sensing, communication, and power transfer.Comment: This paper has been submitted to IEEE for possible publicatio

Towards Text-to-SQL over Aggregate Tables

ABSTRACTText-to-SQL aims at translating textual questions into the corresponding SQL queries. Aggregate tables are widely created for high-frequent queries. Although text-to-SQL has emerged as an important task, recent studies paid little attention to the task over aggregate tables. The increased aggregate tables bring two challenges: (1) mapping of natural language questions and relational databases will suffer from more ambiguity, (2) modern models usually adopt self-attention mechanism to encode database schema and question. The mechanism is of quadratic time complexity, which will make inferring more time-consuming as input sequence length grows. In this paper, we introduce a novel approach named WAGG for text-to-SQL over aggregate tables. To effectively select among ambiguous items, we propose a relation selection mechanism for relation computing. To deal with high computation costs, we introduce a dynamical pruning strategy to discard unrelated items that are common for aggregate tables. We also construct a new large-scale dataset SpiderwAGG extended from Spider dataset for validation, where extensive experiments show the effectiveness and efficiency of our proposed method with 4% increase of accuracy and 15% decrease of inference time w.r.t a strong baseline RAT-SQL

Genome-wide analyses of abiotic stress-related microRNAs and their targets in Arabidopsis thaliana

Abstract MicroRNAs (miRNAs) are known to regulate plant growth and development via regulating gene expression at both transcriptional and post-transcriptional levels. Although several miRNAs have been reported to be associated with abiotic stress responses in plant, systematic investigation of stress-related miRNAs and their targets in plants is limited. In this study, we systematically investigated stress-related miRNAs and their targets in Arabidopsis thaliana. We identified 94 putative stress-related miRNA genes, in which 8 miRNAs were new identified with stress-related response function based on targets prediction. Sequence analysis of these miRNA genes showed that most stress-related miRNAs possess TATA boxes in their promoters, and more than half contain at least two promoters. We also demonstrated that most stress-related miRNA genes contain stress-related elements in their promoters. Furthermore, conservation analysis showed that many stress-related miRNAs are species/family-specific and a subset of stress-related miRNAs may be derived from repeat sequences. Finally, we found that the stress-related miRNAs target 374 genes with 1,153 predicted target sites, of which 87.2% are targeted for gene cleavage and 12.8% affect protein translation. In conclusion, our findings provide an insight into both the function and evolution of stress-related miRNAs

A new metric for measuring the security of an environment: The secrecy pressure

Information-theoretical approaches can ensure security, regardless of the computational power of the attackers. Requirements for the application of this theory are: 1) assuring an advantage over the eavesdropper quality of reception and 2) knowing where the eavesdropper is. The traditional metrics are the secrecy capacity or outage, which are both related to the quality of the legitimate link against the eavesdropper link. Our goal is to define a new metric, which is the characteristic of the security of the surface/environment where the legitimate link is immersed, regardless of the position of the eavesdropping node. The contribution of this paper is twofold: 1) a general framework for the derivation of the secrecy capacity of a surface, which considers all the parameters that influence the secrecy capacity and 2) the definition of a new metric to measure the secrecy of a surface: the secrecy pressure. The metric can be also visualized as a secrecy map, analogously to weather forecast. Different application scenarios are shown: from "forbidden zone" to Gaussian mobility model for the eavesdropper. Moreover, the secrecy outage probability of a surface is derived. This additional metric can measure, which is the secrecy rate supportable by the specific environmentThe work of X. Zhou was supported by the Australian Research Council’s Discovery Projects under Grant DP150103905. The work of Y. Chen was supported by the Guangdong Natural Science Funds under Grant 2016A030313640

Functional Connectivity of Anterior Insula Predicts Recovery of Patients With Disorders of Consciousness

Background: We hypothesize that the anterior insula is important for maintenance of awareness. Here, we explored the functional connectivity alterations of the anterior insula with changes in the consciousness level or over time in patients with disorders of consciousness (DOC) and determined potential correlation with clinical outcomes.Methods: We examined 20 participants (9 patients with DOC and 11 healthy controls). Each patient underwent resting-state functional magnetic resonance imaging (rs-fMRI) and a standardized Coma Recovery Scale-Revised (CRS-R) assessment on the same day. We categorized the patients according to the prognosis: those who emerged from a minimally conscious state (recovery group, n = 4) and those who remained in the unconscious state (unrecovery group, n = 5). Two rs-fMRI scans were obtained from all patients, and the second scan of patients in the recovery group was obtained after they regained consciousness. We performed seed-based fMRI analysis and selected the left ventral agranular insula (vAI) and dorsal agranular insula (dAI) as the regions of interest. Correlations with CRS-R were determined with the Spearman's correlation coefficient.Results: Compared with healthy controls, the functional connectivity between dAI and gyrus rectus of patients who recovered was significantly increased (p < 0.001, cluster-wise family-wise error rate [FWER] < 0.05). The second rs-fMRI scan of patients who remained with DOC showed a significant decreased functional connectivity between the dAI to contralateral insula, pallidum, bilateral inferior parietal lobule (IPL), precentral gyrus, and middle cingulate cortex (p < 0.001, cluster-wise FWER < 0.05) as well as the functional connectivity between vAI to caudate and cingulum contrast to controls (p < 0.001, cluster-wise FWER < 0.05). Finally, the functional connectivity strength of dAI-temporal pole (Spearman r = 0.491, p < 0.05) and dAI-IPL (Spearman r = 0.579, p < 0.05) were positively correlated with CRS-R scores in all DOC patients. The connectivity of dAI-IPL was also positively correlated with clinical scores in the recovery group (Spearman r = 0.807, p < 0.05).Conclusions: Our findings indicate that the recovery of consciousness is associated with an increased connectivity of the dAI to IPL and temporal pole. This possibly highlights the role of the insula in human consciousness. Moreover, longitudinal variations in dAI-IPL and dAI-temporal pole connectivity may be potential hallmarks in the outcome prediction of DOC patients

Dynamic-Fusion Multi-view Projection Clustering Algorithm

Multi-view clustering is a hot research area, which has attracted increasing attention. Most existing multi- view clustering methods usually learn the data first, and then cluster the fused unified graph to get the final result. This two-step strategy of graph learning and graph clustering may lead to the randomness of clustering results. Besides, the inevitable noise of the data itself and the large differences among views, these invalid fusion methods in high-dimensional data space may cause important information loss, and different multi-view data may be sensitive to parameter selections. To solve the above problems, a multi-view projection clustering algorithm based on dynamic fusion is proposed, which integrates adaptive dimensionality reduction graph learning, self-weight fusion without parameters and spectral clustering in the same framework. The three processes promote each other and jointly optimize the projection matrix, similarity matrix, consensus matrix and clustering label. The Laplacian matrix of the best consensus matrix obtained by dynamic fusion is constrained by rank, and clustering results are obtained directly. Moreover, heuristic super-parameters are automatically adjusted with each optimization iteration. To solve the joint optimization problem, an effective alternative optimization method is designed. Experimental results on artificial datasets and real datasets show the superiority of the algorithm

Full-Duplex Backscatter Interference Networks Based on Time-Hopping Spread Spectrum

Future Internet-of-Things (IoT) is expected to wirelessly connect billions of low-complexity devices. For wireless information transfer (IT) in IoT, high density of IoT devices and their ad hoc communication result in strong interference, which acts as a bottleneck on wireless IT. Furthermore, battery replacement for the massive number of IoT devices is difficult if not infeasible, making wireless energy transfer (ET) desirable. This motivates: 1) the design of full-duplex wireless IT to reduce latency and enable efficient spectrum utilization and 2) the implementation of passive IoT devices using backscatter antennas that enable wireless ET from one device (reader) to another (tag). However, the resultant increase in the density of simultaneous links exacerbates the interference issue. This issue is addressed in this paper by proposing the design of full-duplex backscatter communication (BackCom) networks, where a novel multiple-access scheme based on time-hopping spread-spectrum is designed to enable both one-way wireless ET and two-way wireless IT in coexisting backscatter reader-tag links. Comprehensive performance analysis of BackCom networks is presented in this paper, including forward/backward bit-error rates and wireless ET efficiency and outage probabilities, which accounts for energy harvesting at tags, non-coherent and coherent detection at tags and readers, respectively, and the effects of asynchronous transmissions