Information-Theoretic Limits of Integrated Sensing and Communication with Correlated Sensing and Channel States for Vehicular Networks

In connected vehicular networks, it is vital to have vehicular nodes that are capable of sensing about surrounding environments and exchanging messages with each other for automating and coordinating purpose. Towards this end, integrated sensing and communication (ISAC), combining both sensing and communication systems to jointly utilize their resources and to pursue mutual benefits, emerges as a new cost-effective solution. In ISAC, the hardware and spectrum co-sharing leads to a fundamental tradeoff between sensing and communication performance, which is not well understood except for very simple cases with the same sensing and channel states, and perfect channel state information at the receiver (CSIR). In this paper, a general point-to-point ISAC model is proposed to account for the scenarios that the sensing state is different from but correlated with the channel state, and the CSIR is not necessarily perfect. For the model considered, the optimal tradeoff is characterized by a capacity-distortion function that quantifies the best communication rate for a given sensing distortion constraint requirement. An iterative algorithm is proposed to compute such tradeoff, and a few non-trivial examples are constructed to demonstrate the benefits of ISAC as compared to the separation-based approach

Characterization of high exopolysaccharide-producing Lactobacillus strains isolated from mustard pickles for potential probiotic applications

The aim of this study was to characterize high exopolysaccharide (EPS)-producing lactic acid bacteria (LAB) isolated from mustard pickles in Taiwan for potential probiotic applications. Among 39 collected LAB strains, four most productive EPS-producing strains were selected for further analysis. Comparative analyses of 16S rDNA genes rpoA and pheS sequences demonstrated that these strains were members of Lactobacillus plantarum-group (LPG). NCD 2, NLD 4, SLC 13, and NLD 16 showed survival rates of 95.83% ± 0.49%, 95.07% ± 0.64%, 105.84% ± 0.82%, and 99.65% ± 0.31% under simulated gastrointestinal conditions, respectively. No cytotoxic effects on macrophage RAW 264.7 cells were observed when they were treated with a low dose (1 μg/ml) of stimulants extracted from the tested LAB strains. The production of nitric oxide in RAW 264.7 cells incubated with various LAB stimulants showed a dose-dependent increase. Among the four strains, SLC 13 showed higher inhibitory activity on growth of Enterococcus faecalis (BCRC 12302) and Yersinia enterocolitica (BCRC 10807). NLD 4 showed strong inhibitory activity against Escherichia coli O157:H7 (ATCC 43894) as compared with the other three strains. In summary, our results suggest that Lactobacillus pentosus SLC 13 may be a good candidate for probiotic applications and for development of antibacterial compounds. [Int Microbiol 20(2):75-84 (2017)]Keywords: Lactobacillus spp. · exopolysaccharide · probiotic

Tailoring the electrical and thermal conductivity of multi-component and multi-phase polymer composites

The majority of polymers are electrical and thermal insulators. In order to create electrically active and thermally conductive polymers and composites, the hybrid-filler systems is an effective approach, i.e. combining different types of fillers with different dimensions, in order to facilitate the formation of interconnected conducting networks and to enhance the electrical, thermal, mechanical and processing properties synergistically. By tailoring polymer-filler interactions both thermodynamically and kinetically, the selective localisation of fillers in polymer blends and at the interface of co-continuous polymer blends can enhance the electrical conductivity at a low percolation threshold. Moreover, selective localisation of different filler types in different co-continuous phases can result in multiple functionalities, such as high electrical conductivity, thermal conductivity or electromagnetic interference shielding. In this review, we discuss the latest progress towards the development of electrically active and thermally conductive polymer composites, and highlight the technical challenges and future research directions

Msk is required for nuclear import of TGF-{beta}/BMP-activated Smads

Nuclear translocation of Smad proteins is a critical step in signal transduction of transforming growth factor beta (TGF-beta) and bone morphogenetic proteins (BMPs). Using nuclear accumulation of the Drosophila Smad Mothers against Decapentaplegic (Mad) as the readout, we carried out a whole-genome RNAi screening in Drosophila cells. The screen identified moleskin (msk) as important for the nuclear import of phosphorylated Mad. Genetic evidence in the developing eye imaginal discs also demonstrates the critical functions of msk in regulating phospho-Mad. Moreover, knockdown of importin 7 and 8 (Imp7 and 8), the mammalian orthologues of Msk, markedly impaired nuclear accumulation of Smad1 in response to BMP2 and of Smad2/3 in response to TGF-beta. Biochemical studies further suggest that Smads are novel nuclear import substrates of Imp7 and 8. We have thus identified new evolutionarily conserved proteins that are important in the signal transduction of TGF-beta and BMP into the nucleus

Learning to Rank Question Answer Pairs with Holographic Dual LSTM Architecture

We describe a new deep learning architecture for learning to rank question answer pairs. Our approach extends the long short-term memory (LSTM) network with holographic composition to model the relationship between question and answer representations. As opposed to the neural tensor layer that has been adopted recently, the holographic composition provides the benefits of scalable and rich representational learning approach without incurring huge parameter costs. Overall, we present Holographic Dual LSTM (HD-LSTM), a unified architecture for both deep sentence modeling and semantic matching. Essentially, our model is trained end-to-end whereby the parameters of the LSTM are optimized in a way that best explains the correlation between question and answer representations. In addition, our proposed deep learning architecture requires no extensive feature engineering. Via extensive experiments, we show that HD-LSTM outperforms many other neural architectures on two popular benchmark QA datasets. Empirical studies confirm the effectiveness of holographic composition over the neural tensor layer.Comment: SIGIR 2017 Full Pape

Msk is required for nuclear import of TGF-β/BMP-activated Smads

Nuclear translocation of Smad proteins is a critical step in signal transduction of transforming growth factor β (TGF-β) and bone morphogenetic proteins (BMPs). Using nuclear accumulation of the Drosophila Smad Mothers against Decapentaplegic (Mad) as the readout, we carried out a whole-genome RNAi screening in Drosophila cells. The screen identified moleskin (msk) as important for the nuclear import of phosphorylated Mad. Genetic evidence in the developing eye imaginal discs also demonstrates the critical functions of msk in regulating phospho-Mad. Moreover, knockdown of importin 7 and 8 (Imp7 and 8), the mammalian orthologues of Msk, markedly impaired nuclear accumulation of Smad1 in response to BMP2 and of Smad2/3 in response to TGF-β. Biochemical studies further suggest that Smads are novel nuclear import substrates of Imp7 and 8. We have thus identified new evolutionarily conserved proteins that are important in the signal transduction of TGF-β and BMP into the nucleus

Climate drives global soil carbon sequestration and crop yield changes under conservation agriculture

This research was supported by the Natural Science Foundation of China (grant Nos. 41530533 and 41573069) and the National Key R&D Program of China (grant No. 2017YFE0104600). We thank Prof. Xuhui Lee in Yale University, Dr. Zhongkui Luo in Zhejiang University, Prof. Ben Smith in Lund University and Dr. Xunyu Hu in East China Inventory and Planning Institute, State Forestry and Grassland Administration for their helpful comments that led to the improvement of this paper.Peer reviewedPostprin

Probabilistic Constellation Shaping for OFDM-Based ISAC Signaling

Integrated Sensing and Communications (ISAC) has garnered significant attention as a promising technology for the upcoming sixth-generation wireless communication systems (6G). In pursuit of this goal, a common strategy is that a unified waveform, such as Orthogonal Frequency Division Multiplexing (OFDM), should serve dual-functional roles by enabling simultaneous sensing and communications (S&C) operations. However, the sensing performance of an OFDM communication signal is substantially affected by the randomness of the data symbols mapped from bit streams. Therefore, achieving a balance between preserving communication capability (i.e., the randomness) while improving sensing performance remains a challenging task. To cope with this issue, in this paper we analyze the ambiguity function of the OFDM communication signal modulated by random data. Subsequently, a probabilistic constellation shaping (PCS) method is proposed to devise the probability distributions of constellation points, which is able to strike a scalable S&C tradeoff of the random transmitted signal. Finally, the superiority of the proposed PCS method over conventional uniformly distributed constellations is validated through numerical simulations