On the Energy-Efficiency Trade-off Between Active and Passive Communications with RIS-based Symbiotic Radio

Symbiotic radio (SR) is a promising technology of spectrum- and energy-efficient wireless systems, for which the key idea is to use cognitive backscattering communication to achieve mutualistic spectrum and energy sharing with passive backscatter devices (BDs). In this paper, a reconfigurable intelligent surface (RIS) based SR system is considered, where the RIS is used not only to assist the primary active communication, but also for passive communication to transmit its own information. For the considered system, we investigate the EE trade-off between active and passive communications, by characterizing the EE region. To gain some insights, we first derive the maximum achievable individual EEs of the primary transmitter (PT) and RIS, respectively, and then analyze the asymptotic performance by exploiting the channel hardening effect. To characterize the non-trivial EE trade-off, we formulate an optimization problem to find the Pareto boundary of the EE region by jointly optimizing the transmit beamforming, power allocation and the passive beamforming of RIS. The formulated problem is non-convex, and an efficient algorithm is proposed by decomposing it into a series of subproblems by using alternating optimization (AO) and successive convex approximation (SCA) techniques. Finally, simulation results are presented to validate the effectiveness of the proposed algorithm

BadPrompt: Backdoor Attacks on Continuous Prompts

The prompt-based learning paradigm has gained much research attention recently. It has achieved state-of-the-art performance on several NLP tasks, especially in the few-shot scenarios. While steering the downstream tasks, few works have been reported to investigate the security problems of the prompt-based models. In this paper, we conduct the first study on the vulnerability of the continuous prompt learning algorithm to backdoor attacks. We observe that the few-shot scenarios have posed a great challenge to backdoor attacks on the prompt-based models, limiting the usability of existing NLP backdoor methods. To address this challenge, we propose BadPrompt, a lightweight and task-adaptive algorithm, to backdoor attack continuous prompts. Specially, BadPrompt first generates candidate triggers which are indicative for predicting the targeted label and dissimilar to the samples of the non-targeted labels. Then, it automatically selects the most effective and invisible trigger for each sample with an adaptive trigger optimization algorithm. We evaluate the performance of BadPrompt on five datasets and two continuous prompt models. The results exhibit the abilities of BadPrompt to effectively attack continuous prompts while maintaining high performance on the clean test sets, outperforming the baseline models by a large margin. The source code of BadPrompt is publicly available at https://github.com/papersPapers/BadPrompt.Comment: Accepted at NeurIPS 202

Effect of Polymerization Time and Pressure on the Molecular Weight and Molecular Weight Distribution of Polyethylene

Molecular weight and molecular weight distribution (MWD) of polyethylenes (PE) are important in determining their physical, mechanical, and rheological properties of end-products. In principle, molecular weight controls the mechanical properties of polymers, while MWD mainly affects the rheological properties. Therefore, it is necessary to control molecular weight and MWD to optimize the property and processibility of PE. The conventional Ziegler-Natta catalyst is still the main industrial catalyst for the production of PE. Hence, the control of MWD of PE produced using Ziegler-Natta catalyst has always been one of the most worthy research targets for industry and academy. The influence of the polymerization time and pressure on the molecular weight, MWD and relative MWD of PE in the ethylene polymerization with a MgCl2/SiO2/TiCl4/AlEt3 catalyst system in the slurry phase was studied by using gel permeation chromatography (GPC). It has been found that with the lapse of time increases the molecular weight and MWD of PE. However, the increase of the polymerization pressure increases the molecular weight and decreases the MWD of PE

LiSum: Open Source Software License Summarization with Multi-Task Learning

Open source software (OSS) licenses regulate the conditions under which users can reuse, modify, and distribute the software legally. However, there exist various OSS licenses in the community, written in a formal language, which are typically long and complicated to understand. In this paper, we conducted a 661-participants online survey to investigate the perspectives and practices of developers towards OSS licenses. The user study revealed an indeed need for an automated tool to facilitate license understanding. Motivated by the user study and the fast growth of licenses in the community, we propose the first study towards automated license summarization. Specifically, we released the first high quality text summarization dataset and designed two tasks, i.e., license text summarization (LTS), aiming at generating a relatively short summary for an arbitrary license, and license term classification (LTC), focusing on the attitude inference towards a predefined set of key license terms (e.g., Distribute). Aiming at the two tasks, we present LiSum, a multi-task learning method to help developers overcome the obstacles of understanding OSS licenses. Comprehensive experiments demonstrated that the proposed jointly training objective boosted the performance on both tasks, surpassing state-of-the-art baselines with gains of at least 5 points w.r.t. F1 scores of four summarization metrics and achieving 95.13% micro average F1 score for classification simultaneously. We released all the datasets, the replication package, and the questionnaires for the community

Targeting oncogenic miR-335 inhibits growth and invasion of malignant astrocytoma cells

<p>Abstract</p> <p>Background</p> <p>Astrocytomas are the most common and aggressive brain tumors characterized by their highly invasive growth. Gain of chromosome 7 with a hot spot at 7q32 appears to be the most prominent aberration in astrocytoma. Previously reports have shown that microRNA-335 (miR-335) resided on chromosome 7q32 is deregulated in many cancers; however, the biological function of miR-335 in astrocytoma has yet to be elucidated.</p> <p>Results</p> <p>We report that miR-335 acts as a tumor promoter in conferring tumorigenic features such as growth and invasion on malignant astrocytoma. The miR-335 level is highly elevated in C6 astrocytoma cells and human malignant astrocytomas. Ectopic expression of miR-335 in C6 cells dramatically enhances cell viability, colony-forming ability and invasiveness. Conversely, delivery of antagonist specific for miR-335 (antagomir-335) to C6 cells results in growth arrest, cell apoptosis, invasion repression and marked regression of astrocytoma xenografts. Further investigation reveals that miR-335 targets disheveled-associated activator of morphogenesis 1(Daam1) at posttranscriptional level. Moreover, silencing of endogenous Daam1 (siDaam1) could mimic the oncogenic effects of miR-335 and reverse the growth arrest, proapoptotic and invasion repression effects induced by antagomir-335. Notably, the oncogenic effects of miR-335 and siDAAM1 together with anti-tumor effects of antagomir-335 are also confirmed in human astrocytoma U87-MG cells.</p> <p>Conclusion</p> <p>These findings suggest an oncogenic role of miR-335 and shed new lights on the therapy of malignant astrocytomas by targeting miR-335.</p