Meta-Gating Framework for Fast and Continuous Resource Optimization in Dynamic Wireless Environments

With the great success of deep learning (DL) in image classification, speech recognition, and other fields, more and more studies have applied various neural networks (NNs) to wireless resource allocation. Generally speaking, these artificial intelligent (AI) models are trained under some special learning hypotheses, especially that the statistics of the training data are static during the training stage. However, the distribution of channel state information (CSI) is constantly changing in the real-world wireless communication environment. Therefore, it is essential to study effective dynamic DL technologies to solve wireless resource allocation problems. In this paper, we propose a novel framework, named meta-gating, for solving resource allocation problems in an episodically dynamic wireless environment, where the CSI distribution changes over periods and remains constant within each period. The proposed framework, consisting of an inner network and an outer network, aims to adapt to the dynamic wireless environment by achieving three important goals, i.e., seamlessness, quickness and continuity. Specifically, for the former two goals, we propose a training method by combining a model-agnostic meta-learning (MAML) algorithm with an unsupervised learning mechanism. With this training method, the inner network is able to fast adapt to different channel distributions because of the good initialization. As for the goal of continuity, the outer network can learn to evaluate the importance of inner network's parameters under different CSI distributions, and then decide which subset of the inner network should be activated through the gating operation. Additionally, we theoretically analyze the performance of the proposed meta-gating framework.Comment: accepted by IEEE TCO

Probably Anytime-Safe Stochastic Combinatorial Semi-Bandits

Motivated by concerns about making online decisions that incur undue amount of risk at each time step, in this paper, we formulate the probably anytime-safe stochastic combinatorial semi-bandits problem. In this problem, the agent is given the option to select a subset of size at most $K$ from a set of $L$ ground items. Each item is associated to a certain mean reward as well as a variance that represents its risk. To mitigate the risk that the agent incurs, we require that with probability at least $1-\delta$, over the entire horizon of time $T$, each of the choices that the agent makes should contain items whose sum of variances does not exceed a certain variance budget. We call this probably anytime-safe constraint. Under this constraint, we design and analyze an algorithm {\sc PASCombUCB} that minimizes the regret over the horizon of time $T$. By developing accompanying information-theoretic lower bounds, we show that under both the problem-dependent and problem-independent paradigms, {\sc PASCombUCB} is almost asymptotically optimal. Experiments are conducted to corroborate our theoretical findings. Our problem setup, the proposed {\sc PASCombUCB} algorithm, and novel analyses are applicable to domains such as recommendation systems and transportation in which an agent is allowed to choose multiple items at a single time step and wishes to control the risk over the whole time horizon.Comment: To be presented at ICML 2023. 57 pages, 6 figure

MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning

Prompt-based learning reformulates downstream tasks as cloze problems by combining the original input with a template. This technique is particularly useful in few-shot learning, where a model is trained on a limited amount of data. However, the limited templates and text used in few-shot prompt-based learning still leave significant room for performance improvement. Additionally, existing methods using model ensembles can constrain the model efficiency. To address these issues, we propose an augmentation method called MixPro, which augments both the vanilla input text and the templates through token-level, sentence-level, and epoch-level Mixup strategies. We conduct experiments on five few-shot datasets, and the results show that MixPro outperforms other augmentation baselines, improving model performance by an average of 5.08% compared to before augmentation.Comment: Under review at the Frontiers of Computer Science (https://www.springer.com/journal/11704/); 14 pages, 4 figures, 5 table

Bioactivity-guided fractionation of the triglyceride-lowering component and in vivo and in vitro evaluation of hypolipidemic effects of Calyx seu Fructus Physalis

<p>Abstract</p> <p>Background</p> <p>In folklore, some people take the decoction of <it>Calyx seu Fructus Physalis </it>(CSFP) for lowering blood lipids. The present study is designed to evaluate the lipid-lowering activities of CSFP, and search for its pharmacodynamical material.</p> <p>Methods</p> <p>CSFP was extracted by water and 75% ethanol, respectively. The extracts of CSFP for reducing serum lipid levels were evaluated on mouse model of hyperlipidemia. The optimized extract was subjected to the bioactivity-guided fractionation in which the liquid-liquid extraction, collumn chromatography, the <it>in vivo </it>and <it>in vitro </it>models of hyperlipidemia were utilized. The structure of active component was determined by ¹³C-NMR and ¹H-NMR.</p> <p>Results</p> <p>The 75% ethanol extract of CSFP decreased the serum total cholesterol (TC) and triglyceride (TG) levels in mouse model of hyperlipidemia. Followed a separation process for the 75% ethanol extract of CSFP, the fraction B was proved to be an active fraction for lowering lipid <it>in vivo </it>and <it>in vitro </it>experiments, which could significantly decrease the serum TC and TG levels in mouse model of hyperlipidemia, and remarkably decrease the increase of TG in primary mouse hepatocytes induced by high glucose and the increase of TG in HepG2 cells induced by oleic acid. The fraction B2, isolated from B on bioactivity-guided fractionation, could significantly decrease TG level in HepG2 cells. One compound with the highest content in B2 was isolated and determined as luteolin-7-O-beta-D-glucopyranoside by NMR spectra. It could significantly reduce the TG level in HepG2 cells, and inhibited the accumulation of lipids by oil red O stain.</p> <p>Conclusion</p> <p>Our results demonstrated that the 75% ethanol extract of CSFP could improve <it>in vitro </it>and <it>in vivo </it>lipid accumulation. Luteolin-7-O-beta-D-glucopyranoside might be a leading pharmacodynamical material of CSFP for lowering lipids.</p

In-situ synthesis of ultra-fine ZrB2–ZrC–SiC nanopowders by sol-gel method

© 2019 Elsevier Ltd and Techna Group S.r.l. ZrB2–ZrC–SiC nanopowders with uniform phase distribution were prepared from cost-effective ZrOCl2·8H2O by a simple sol-gel method. The synthesis route, ceramization mechanism and morphology evolution of the nanopowders were investigated. ZrB2–ZrC–SiC ceramic precursor can be successfully obtained through hydrolysis and condensation reactions between the raw materials. Pyrolysis of the precursor was completed at 650 °C, and it produced ZrO2, SiO2, B2O3 and amorphous carbon with a yield of 39% at 1300 °C. By heat-treated at 1500 °C for 2 h, highly crystallized ZrB2–ZrC–SiC ceramics with narrow size distribution were obtained. With the holding time of 2 h, both the crystal size and the particle size can be refined. Further prolonging the holding time can lead to serious particles coarsening. Studies on the microstructure evolution of the generated carbon during the ceramic conversion demonstrates the negative effect of the ceramic formation on the structure order improvement of the carbon, due to the large amount of defects generated in it by the boro/carbothermal reduction reactions

Diagnostic and prognostic value of serum C-reactive protein in heart failure with preserved ejection fraction:a systematic review and meta-analysis

Heart failure (HF) is a major epidemic with rising morbidity and mortality rates that encumber global healthcare systems. While some studies have demonstrated the value of CRP in predicting (i) the development of HFpEF and (ii) long-term clinical outcomes in HFpEF patients, others have shown no such correlation. As a result, we conducted the following systematic review and meta-analysis to assess both the diagnostic and prognostic role of CRP in HFpEF. PubMed and Embase were searched for studies that assess the relationship between CRP and HFpEF using the following search terms: (((C-reactive protein) AND ((preserved ejection fraction) OR (diastolic heart failure))). The search period was from the start of database to August 6, 2019, with no language restrictions. A total of 312 and 233 studies were obtained from PubMed and Embase respectively, from which 19 studies were included. Our meta-analysis demonstrated the value of a high CRP in predicting the development of not only new onset HFpEF (HR: 1.08; 95% CI: 1.00–1.16; P = 0.04; I 2 = 22%), but also an increased risk of cardiovascular mortality when used as a categorical (HR: 2.52; 95% CI: 1.61–3.96; P < 0.0001; I 2 = 19%) or a continuous variable (HR: 1.24; 95% CI: 1.04–1.47; P = 0.01; I 2 = 28%), as well as all-cause mortality when used as a categorical (HR: 1.78; 95% CI: 1.53–2.06; P < 0.00001; I 2 = 0%) or a continuous variable: (HR: 1.06; 95% CI: 1.02–1.06; P = 0.003; I 2 = 61%) in HFpEF patients. CRP can be used as a biomarker to predict the development of HFpEF and long-term clinical outcomes in HFpEF patients, in turn justifying its use as a simple, accessible parameter to guide clinical management in this patient population. However, more prospective studies are still required to not only explore the utility and dynamicity of CRP in HFpEF but also to determine whether risk stratification algorithms incorporating CRP actually provide a material benefit in improving patient prognosis

Starvation sensing by mycobacterial RelA/SpoT homologue through constitutive surveillance of translation

The stringent response, which leads to persistence of nutrient-starved mycobacteria, is induced by activation of the RelA/SpoT homolog (Rsh) upon entry of a deacylated-tRNA in a translating ribosome. However, the mechanism by which Rsh identifies such ribosomes in vivo remains unclear. Here, we show that conditions inducing ribosome hibernation result in loss of intracellular Rsh in a Clp protease-dependent manner. This loss is also observed in nonstarved cells using mutations in Rsh that block its interaction with the ribosome, indicating that Rsh association with the ribosome is important for Rsh stability. The cryo-EM structure of the Rsh-bound 70S ribosome in a translation initiation complex reveals unknown interactions between the ACT domain of Rsh and components of the ribosomal L7/L12 stalk base, suggesting that the aminoacylation status of A-site tRNA is surveilled during the first cycle of elongation. Altogether, we propose a surveillance model of Rsh activation that originates from its constitutive interaction with the ribosomes entering the translation cycle