L2L_2-Box Optimization for Green Cloud-RAN via Network Adaptation

In this paper, we propose a reformulation for the Mixed Integer Programming (MIP) problem into an exact and continuous model through using the $\ell_2$-box technique to recast the binary constraints into a box with an $\ell_2$ sphere constraint. The reformulated problem can be tackled by a dual ascent algorithm combined with a Majorization-Minimization (MM) method for the subproblems to solve the network power consumption problem of the Cloud Radio Access Network (Cloud-RAN), and which leads to solving a sequence of Difference of Convex (DC) subproblems handled by an inexact MM algorithm. After obtaining the final solution, we use it as the initial result of the bi-section Group Sparse Beamforming (GSBF) algorithm to promote the group-sparsity of beamformers, rather than using the weighted $\ell_1 / \ell_2$-norm. Simulation results indicate that the new method outperforms the bi-section GSBF algorithm by achieving smaller network power consumption, especially in sparser cases, i.e., Cloud-RANs with a lot of Remote Radio Heads (RRHs) but fewer users.Comment: 4 pages, 4 figure

Bank Capital, Bank Lending and Monetary Policy in the United States

This paper examines the relationship between banks lending and monetary policy for banks with different level of capital ratio. We study the relation using the sample of U.S. banks over the period 1994 to 2010. We choose short term interest rate, deposit, security and GDP as components of monetary policy. We use bank loan change as the dependent variable, short term interest rate, deposit, security, GDP change and 1 year lagged change as independent variables for the regression model. Our model returns significant results for all independent variables except security change lagged variable for all three categories and short term interest rate variable for best-capitalized banks. Out finding shows that the monetary policy change will significantly affect bank lending change with strongest effect on least-capitalized banks and weakest effect on best-capitalized banks

An Auction-based Mechanism for Cooperative Sensing in Cognitive Networks

International audienceIn this paper, we propose an auction-based cooperative sensing protocol for secondary users in cognitive networks. The proposed auction mechanism is based on a novel modified Vickrey auction with a three dimensional bid, that accounts for detection gains as well as for virtual currency gains. We present a formal proof to show that the proposed three dimensional bidding mechanism preserves the truthfulness property of the classic Vickrey auction. The cooperative auction is combined with a prioritized access scheme to increase the efficiency and to reduce the response time for the coalition formation procedure. Our auction-based cooperative sensing mechanism can be easily applied to different network scenarios, by defining specific utility functions. The proposed cooperative sensing auctioning mechanism is illustrated for both downlink and uplink. Our simulation results show that users' cooperation is incentivized by the proposed algorithm, which leads to significant detection gains for the downlink and the uplink scenarios, with a more efficient energy expenditure

Comparative studies of computation tools for moving force

Existing techniques to identify moving forces based on traditional finite element method (TFEM) is subject to a large number of elements with detailed description of a structure, which makes modeling complicated. A new modeling method for a vehicle-bridge system called wavelet finite element method (WFEM) is presented in this paper. It makes use of a multi-scale analysis whereby detailed description can be achieved to overcome this problem. The shape function of WFEM is formed by a scale function in a wavelet space and by a transformation matrix to connect the wavelet space to the physical one. To evaluate the properties of WFEM, simulations of two moving forces on a simply supported and a continuous bridge are conducted with subsequent comparison with TFEM. To smooth the noise and large fluctuations on the boundaries of the identified results in the time history, the first-order Tikhonov regularizations combined with the dynamic programming technique are adapted and compared with the zeroth-order Tikhonov regularization. White noise is added to the simulated dynamic responses. Some parameter effects, such as vehicle bridge parameters, measurement parameters are also considered. Numerical results demonstrate the WFEM method and the first-order Tikhonov regularization method to be effective for moving force identification. The first-order Tikhonov regularization has the property of smoothing noise and avoiding large fluctuations on the boundaries. Meanwhile, the parameters analyzed affect the identified results to some extent

The Asian arowana (Scleropages formosus) genome provides new insights into the evolution of an early lineage of teleosts

The Asian arowana (Scleropages formosus), one of the world’s most expensive cultivated ornamental fishes, is an endangered species. It represents an ancient lineage of teleosts: the Osteoglossomorpha. Here, we provide a high-quality chromosome-level reference genome of a female golden-variety arowana using a combination of deep shotgun sequencing and high-resolution linkage mapping. In addition, we have also generated two draft genome assemblies for the red and green varieties. Phylogenomic analysis supports a sister group relationship between Osteoglossomorpha (bonytongues) and Elopomorpha (eels and relatives), with the two clades together forming a sister group of Clupeocephala which includes all the remaining teleosts. The arowana genome retains the full complement of eight Hox clusters unlike the African butterfly fish (Pantodon buchholzi), another bonytongue fish, which possess only five Hox clusters. Differential gene expression among three varieties provides insights into the genetic basis of colour variation. A potential heterogametic sex chromosome is identified in the female arowana karyotype, suggesting that the sex is determined by a ZW/ZZ sex chromosomal system. The high-quality reference genome of the golden arowana and the draft assemblies of the red and green varieties are valuable resources for understanding the biology, adaptation and behaviour of Asian arowanas

Transcriptomic and gene-family dynamic analyses reveal gene expression pattern and evolution in toxin-producing tissues of Asiatic toad (Bufo gargarizans)

Comprising a major clade of Anura, toads produce and secrete numerous toxins from both the parotoid glands behind their eyes and their dorsal skin. These toxins, made of various proteins and compounds, possess pharmacological potential to be repurposed to benefit human health. However, the detailed genetic regulation of toad toxin production is still poorly understood. A recent publication uncovering the genome of the representative Asiatic toad (Bufo gargarizans) provides a good reference to resolve this issue. In the present study, we sequenced the transcriptomes of parotoid gland, dorsal skin and liver from the Asiatic toad. Combining our data with 35 previously published transcriptomes across eight different tissues from the same species but from different locations, we constructed a comprehensive gene co-expression network of the Asiatic toad with the assistance of the reference genome assembly. We identified 2,701 co-expressed genes in the toxin-producing tissues (including parotoid gland and dorsal skin). By comparative genomic analysis, we identified 599 expanded gene families with 2,720 genes. Through overlapping these co-expressed genes in the toad toxin-producing tissues, we observed that three cytochrome P450 (Cyp) family members (Cyp27a1, Cyp2c29, and Cyp2c39) were significantly enriched in pathways related to cholesterol metabolism. Cholesterol is a critical precursor to steroids, and the known main steroidal toxins of bufadienolides are considered as the major bioactive components in the parotoid glands of Asiatic toad. We found 3-hydroxy-methylglutaryl CoA reductase (hmgcr), encoding the major rate-limiting enzyme for cholesterol biosynthesis, appears with multiple copies in both Asiatic toad and common toad, possibly originating from a tandem duplication event. The five copies of hmgcr genes consistently displayed higher transcription levels in the parotoid gland when compared with the abdominal skin, suggesting it as a vital candidate gene in the involvement of toad toxin production. Taken together, our current study uncovers transcriptomic and gene-family dynamic evidence to reveal the vital role of both expanded gene copies and gene expression changes for production of toad toxins

Association between PNPLA8 gene polymorphism and schizophrenia in male patients

Abnormal phospholipid metabolism in the brain plays an important role in neuropsychiatric diseases. Phospholipase A2 is crucial for maintaining normal neuro-physiological function. The aim of this study was to investigate the association between polymorphisms of the membrane-associated calcium-independent phospholipase A2 gamma (PNPLA8) gene and schizophrenia in Han Chinese in north China. The PCR-based ligase detection reaction was applied to detect 3 single nucleotide polymorphisms (SNPs) in the PNPLA8 gene among 201 Chinese pedigrees. The genotypic frequency of the PNPLA8 polymorphisms did not deviate from the Hardy-Weinberg equilibrium both in affected offspring and parental groups. Haploid relative risk (HRR) and transmission disequilibrium tests (TDT) showed that the 3 SNPs were not associated with schizophrenia (p>0.05), but further analysis with TDT showed that the rs40876 polymorphism was associated with schizophrenia in males (χ2=4.667, p=0.031). Our data suggest that rs40876 in PNPLA8 may be associated with schizophrenia in males

Towards V2I Age-aware Fairness Access: A DQN Based Intelligent Vehicular Node Training and Test Method

Vehicles on the road exchange data with base station (BS) frequently through vehicle to infrastructure (V2I) communications to ensure the normal use of vehicular applications, where the IEEE 802.11 distributed coordination function (DCF) is employed to allocate a minimum contention window (MCW) for channel access. Each vehicle may change its MCW to achieve more access opportunities at the expense of others, which results in unfair communication performance. Moreover, the key access parameters MCW is the privacy information and each vehicle are not willing to share it with other vehicles. In this uncertain setting, age of information (AoI) is an important communication metric to measure the freshness of data, we design an intelligent vehicular node to learn the dynamic environment and predict the optimal MCW which can make it achieve age fairness. In order to allocate the optimal MCW for the vehicular node, we employ a learning algorithm to make a desirable decision by learning from replay history data. In particular, the algorithm is proposed by extending the traditional DQN training and testing method. Finally, by comparing with other methods, it is proved that the proposed DQN method can significantly improve the age fairness of the intelligent node.Comment: This paper has been accepted by Chinese Journal of Electronics. Simulation codes have been provided at: https://github.com/qiongwu86/Age-Fairnes