On the Performance of Spectrum Sensing Algorithms using Multiple Antennas

In recent years, some spectrum sensing algorithms using multiple antennas, such as the eigenvalue based detection (EBD), have attracted a lot of attention. In this paper, we are interested in deriving the asymptotic distributions of the test statistics of the EBD algorithms. Two EBD algorithms using sample covariance matrices are considered: maximum eigenvalue detection (MED) and condition number detection (CND). The earlier studies usually assume that the number of antennas (K) and the number of samples (N) are both large, thus random matrix theory (RMT) can be used to derive the asymptotic distributions of the maximum and minimum eigenvalues of the sample covariance matrices. While assuming the number of antennas being large simplifies the derivations, in practice, the number of antennas equipped at a single secondary user is usually small, say 2 or 3, and once designed, this antenna number is fixed. Thus in this paper, our objective is to derive the asymptotic distributions of the eigenvalues and condition numbers of the sample covariance matrices for any fixed K but large N, from which the probability of detection and probability of false alarm can be obtained. The proposed methodology can also be used to analyze the performance of other EBD algorithms. Finally, computer simulations are presented to validate the accuracy of the derived results.Comment: IEEE GlobeCom 201

Spectrum Sensing Algorithms for Cognitive Radio Based on Statistical Covariances

Spectrum sensing, i.e., detecting the presence of primary users in a licensed spectrum, is a fundamental problem in cognitive radio. Since the statistical covariances of received signal and noise are usually different, they can be used to differentiate the case where the primary user's signal is present from the case where there is only noise. In this paper, spectrum sensing algorithms are proposed based on the sample covariance matrix calculated from a limited number of received signal samples. Two test statistics are then extracted from the sample covariance matrix. A decision on the signal presence is made by comparing the two test statistics. Theoretical analysis for the proposed algorithms is given. Detection probability and associated threshold are found based on statistical theory. The methods do not need any information of the signal, the channel and noise power a priori. Also, no synchronization is needed. Simulations based on narrowband signals, captured digital television (DTV) signals and multiple antenna signals are presented to verify the methods

Discovery of a Novel Analogue of FR901533 and the Corresponding Biosynthetic Gene Cluster From Streptosporangium Roseum No. 79089

FR901533 (1, also known as WS79089B), WS79089A (2), and WS79089C (3) are polycyclic aromatic natural products with promising inhibitory activity to endothelin-converting enzymes. In this work, we isolated five tridecaketide products from Streptosporangium roseum No. 79089, including 1-3, benaphthamycin (4) and a novel FR901533 analogue (5). The structure of 5 was characterized based on spectroscopic data. Compared to the major product 2, the new compound 5 has an additional hydroxyl group at C-12 and an extra methyl group at the 13-OH. The configuration of C-19 of these compounds was determined to be R using Mosher\u27s method. A putative biosynthetic gene cluster for compounds 1-5 was discovered by analyzing the genome of S. roseum No. 79089. This 38.6-kb gene cluster contains 38 open reading frames, including a minimal polyketide synthase (wsaA-C), an aromatase (wsaD), three cyclases (wsaE, F and W) and a series of tailoring enzymes such as monooxygenases (wsaO1-O7) and methyltransferases (wsaM1 and M2). Disruption of the ketosynthase gene (wsaA) in this gene cluster abolished the production of 1-5, confirming that this gene cluster is indeed responsible for the biosynthesis of 1-5. A type II polyketide biosynthetic pathway was proposed for this group of natural endothelin-converting enzyme inhibitors

Phylogenetic structure and formation mechanism of shrub communities in arid and semiarid areas of the Mongolian Plateau

The mechanisms of species coexistence within a community have always been the focus in ecological research. Community phylogenetic structure reflects the relationship of historical processes, regional environments, and interactions between species, and studying it is imperative to understand the formation and maintenance mechanisms of community composition and biodiversity. We studied the phylogenetic structure of the shrub communities in arid and semiarid areas of the Mongolian Plateau. First, the phylogenetic signals of four plant traits (height, canopy, leaf length, and leaf width) of shrubs and subshrubs were measured to determine the phylogenetic conservation of these traits. Then, the net relatedness index (NRI) of shrub communities was calculated to characterize their phylogenetic structure. Finally, the relationship between the NRI and current climate and paleoclimate (since the Last Glacial Maximum, LGM) factors was analyzed to understand the formation and maintenance mechanisms of these plant communities. We found that desert shrub communities showed a trend toward phylogenetic overdispersion; that is, limiting similarity was predominant in arid and semiarid areas of the Mongolian Plateau despite the phylogenetic structure and formation mechanisms differing across habitats. The typical desert and sandy shrub communities showed a significant phylogenetic overdispersion, while the steppified desert shrub communities showed a weak phylogenetic clustering. It was found that mean winter temperature (i.e., in the driest quarter) was the major factor limiting steppified desert shrub phylogeny distribution. Both cold and drought (despite having opposite consequences) differentiated the typical desert to steppified desert shrub communities. The increase in temperature since the LGM is conducive to the invasion of shrub plants into steppe grassland, and this process may be intensified by global warming

Robust multi-atlas label propagation by deep sparse representation

Recently, multi-atlas patch-based label fusion has achieved many successes in medical imaging area. The basic assumption in the current state-of-the-art approaches is that the image patch at the target image point can be represented by a patch dictionary consisting of atlas patches from registered atlas images. Therefore, the label at the target image point can be determined by fusing labels of atlas image patches with similar anatomical structures. However, such assumption on image patch representation does not always hold in label fusion since (1) the image content within the patch may be corrupted due to noise and artifact; and (2) the distribution of morphometric patterns among atlas patches might be unbalanced such that the majority patterns can dominate label fusion result over other minority patterns. The violation of the above basic assumptions could significantly undermine the label fusion accuracy. To overcome these issues, we first consider forming label-specific group for the atlas patches with the same label. Then, we alter the conventional flat and shallow dictionary to a deep multi-layer structure, where the top layer (label-specific dictionaries) consists of groups of representative atlas patches and the subsequent layers (residual dictionaries) hierarchically encode the patchwise residual information in different scales. Thus, the label fusion follows the representation consensus across representative dictionaries. However, the representation of target patch in each group is iteratively optimized by using the representative atlas patches in each label-specific dictionary exclusively to match the principal patterns and also using all residual patterns across groups collaboratively to overcome the issue that some groups might be absent of certain variation patterns presented in the target image patch. Promising segmentation results have been achieved in labeling hippocampus on ADNI dataset, as well as basal ganglia and brainstem structures, compared to other counterpart label fusion methods

Gut Bacterial Communities of Lymantria xylina and Their Associations with Host Development and Diet

The gut microbiota of insects has a wide range of effects on host nutrition, physiology, and behavior. The structure of gut microbiota may also be shaped by their environment, causing them to adjust to their hosts; thus, the objective of this study was to examine variations in the morphological traits and gut microbiota of Lymantria xylina in response to natural and artificial diets using high-throughput sequencing. Regarding morphology, the head widths for larvae fed on a sterilized artificial diet were smaller than for larvae fed on a non-sterilized host-plant diet in the early instars. The gut microbiota diversity of L. xylina fed on different diets varied significantly, but did not change during different development periods. This seemed to indicate that vertical inheritance occurred in L. xylina mutualistic symbionts. Acinetobacter and Enterococcus were dominant in/on eggs. In the first instar larvae, Acinetobacter accounted for 33.52% of the sterilized artificial diet treatment, while Enterococcus (67.88%) was the predominant bacteria for the non-sterilized host-plant diet treatment. Gut microbe structures were adapted to both diets through vertical inheritance and self-regulation. This study clarified the impacts of microbial symbiosis on L. xylina and might provide new possibilities for improving the control of these bacteria

Trap-Assisted Charge Injection into Large Bandgap Polymer Semiconductors.

The trap-assisted charge injection in polyfluorene-poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS) model systems with an Al or Al/LiF cathode is investigated. We find that inserting 1.3 nm LiF increases electron and hole injections simultaneously and the increase of holes is greater than electrons. The evolution of internal interfaces within polymer light-emitting diodes is observed by transmission electron microscopy, which reveals that the introduction of LiF improves the interface stability at both the cathode (cathode/polymer) and the anode (indium tin oxide (ITO)/PEDOT:PSS). Above-mentioned experimental results have been compared to the numerical simulations with a revised Davids model and potential physical mechanisms for the trap-assisted charge injection are discussed

Modified Substrate Specificity of a Methyltransferase Domain by Protein Insertion Into an Adenylation Domain of the Bassianolide Synthetase

Background: Creating designer molecules using a combination of select domains from polyketide synthases and/or nonribosomal peptide synthetases (NRPS) continues to be a synthetic goal. However, an incomplete understanding of how protein-protein interactions and dynamics affect each of the domain functions stands as a major obstacle in the field. Of particular interest is understanding the basis for a class of methyltransferase domains (MT) that are found embedded within the adenylation domain (A) of fungal NRPS systems instead of in an end-to-end architecture. Results: The MT domain from bassianolide synthetase (BSLS) was removed and the truncated enzyme BSLS-ΔMT was recombinantly expressed. The biosynthesis of bassianolide was abolished and N-desmethylbassianolide was produced in low yields. Co-expression of BSLS-ΔMT with standalone MT did not recover bassianolide biosynthesis. In order to address the functional implications of the protein insertion, we characterized the N-methyltransferase activity of the MT domain as both the isolated domain (MTBSLS) and as part of the full NRPS megaenzyme. Surprisingly, the MTBSLS construct demonstrated a relaxed substrate specificity and preferentially methylated an amino acid (L-Phe-SNAC) that is rarely incorporated into the final product. By testing the preference of a series of MT constructs (BSLS, MTBSLS, cMT, XLcMT, and aMT) to L-Phe-SNAC and L-Leu-SNAC, we further showed that restricting and/or fixing the termini of the MTBSLS by crosslinking or embedding the MT within an A domain narrowed the substrate specificity of the methyltransferase toward L-Leu-SNAC, the preferred substrate for the BSLS megaenzyme. Conclusions: The embedding of MT into the A2 domain of BSLS is not required for the product assembly, but is critical for the overall yields of the final products. The substrate specificity of MT is significantly affected by the protein context within which it is present. While A domains are known to be responsible for selecting and activating the biosynthetic precursors for NRPS systems, our results suggest that embedding the MT acts as a secondary gatekeeper for the assembly line. This work thus provides new insights into the embedded MT domain in NRPSs, which will facilitate further engineering of this type of biosynthetic machinery to create structural diversity in natural products

Effluent-free deep dyeing of cotton fabric with cacao husk extracts using the Taguchi optimization method

Textile dyehouses are under scrutiny because they discharge colored and hazardous effluents to waterways. There is a need to develop an alternative dyeing system that does not produce any hazardous effluent. The waterless dyeing method could be a viable eco-friendly alternative to the traditional aqueous dyeing method. In this work, cacao husk extracts were used as a natural dye in the decamethylcyclopentasiloxane (D5) medium for the dyeing of cotton fabric, and subsequently, the dyed cotton was treated by a fixation treatment with a cationic dye-fixing agent in the D5 medium. The cotton fabric dyed with cacao husk extracts exhaustion in the waterless D5 medium exhibited better exhaustion, fixation rate, color strength (K/S), and colorfastness to washing and rubbing compared to the fabric dyed with the same extracts using the conventional aqueous dyeing and dye-fixing methods. The dye exhaustion percentage and the dye fixation rate were 95.6% and 94.8% in the D5 medium respectively, which is significantly higher in comparison to a 48.2% dye exhaustion percentage and a 35.3% dye fixation rate in the conventional water medium. An orthogonal array design (L9) was adopted to optimize the dyeing conditions with respect to exhaustion percentage. The results indicated that the dyebath temperature was the most important factor for achieving the optimal dye exhaustion, and dyeing time also showed considerable effects. Linear regression was used to predict the exhaustion percentage, and the resulting p value of 0.000 demonstrated that a strong coefficient was proven among all selected factors. This study has demonstrated that dyeing of cotton fabric with cacao husk extracts in the D5 dyeing system can be a viable method for the textile industry with minimal environmental pollution