Optical Monitoring of BL Lacertae Object S5 0716+714 with a Novel Multi-Peak Interference Filter

We at first introduce a novel photometric system, which consists of a Schmidt telescope, an objective prism, a CCD camera, and, especially, a multi-peak interference filter. The multi-peak interference filter enables light in multi passbands to pass through it simultaneously. The light in different passbands is differentially refracted by the objective prism and is focused on the CCD separately, so we have multi "images" for each object on the CCD frames. This system enables us to monitor blazars exactly simultaneously in multi wavebands on a single telescope, and to accurately trace the color change during the variation. We used this novel system to monitor the BL Lacertae object S5 0716+714 during 2006 January and February and achieved a very high temporal resolution. The object was very bright and very active during this period. Two strong flares were observed, with variation amplitudes of about 0.8 and 0.6 mags in the $V'$ band, respectively. Strong bluer-when-brighter correlations were found for both internight and intranight variations. No apparent time lag was observed between the $V'$- and $R'$-band variations, and the observed bluer-when-brighter chromatism may be mainly attributed to the larger variation amplitude at shorter wavelength. In addition to the bluer-when-brighter trend, the object also showed a bluer color when it was more active. The observed variability and its color behaviors are consistent with the shock-in-jet model.Comment: 30 pages, 22 figures, accepted by A

A Sum-Utility Maximization Approach for Fairness Resource Allocation in Wireless Powered Body Area Networks

Wireless body area networks (WBANs) are essential for monitoring physiological signals of the human body, but the lifetime of WBANs is limited by battery longevity and it is not convenient or feasible for replacing the batteries of the sensors. The newly emerged energy-harvesting technology provides the potential to break the battery limitation of WBANs. However, the radio resource of a WBAN should be carefully scheduled for the wireless power transfer links and wireless information transmission links; otherwise, severely unfair resource allocation could be incurred due to the difference of channel qualities of the sensors. In this paper, we propose a marginal utility theoretic method to allocate the radio resource to the on-/in-body sensors in a fair and efficient manner. Especially, we consider that the sensors are wireless powered by multiple pre-installed radio-frequency energy sources. First, the utility function for a sensor node is proposed, which can map the achievable throughput to a satisfaction level of network QoS. Then, the fairness resource allocation among the sensor nodes is modeled as a sum-utility maximization problem. By using the dual decomposition method, the optimal solution to the proposed problem can finally be solved in the closed form. In comparison with the sum-throughput maximization and common-throughput maximization methods, the simulation results show that the proposed sum-utility maximization method can bring a fair throughput allocation for the sensors with different channel conditions, and the performance loss to the sum-throughput maximization method is small, while the sum-throughput maximization method is extremely unfair

Blind image quality assessment for authentic distortions by intermediary enhancement and iterative training

With the boom of deep neural networks, blind image quality assessment (BIQA) has achieved great processes. However, the current BIQA metrics are limited when evaluating low-quality images as compared to medium-quality and high-quality images, which restricts their applications in real world problems. In this paper, we first identify that two challenges caused by distribution shift and long-tailed distribution lead to the compromised performance on low-quality images. Then, we propose an intermediary enhancement-based bilateral network with iterative training strategy for solving these two challenges. Drawing on the experience of transitive transfer learning, the proposed metric adaptively introduces enhanced intermediary images to transfer more information to low-quality images for mitigating the distribution shift. Our metric also adopts an iterative training strategy to deal with the long-tailed distribution. This strategy decouples feature extraction and score regression for better representation learning and regressor training. It not only transfers the knowledge learned from the earlier stage to the latter stage, but also makes the model pay more attention to long-tailed low-quality images. We conduct extensive experiments on five authentically distorted image quality datasets. The results show that our metric significantly improves the evaluating performance on low-quality images and delivers state-of-the-art intra-dataset results. During generalization tests, our metric also achieves the best cross-dataset performanc

Multimodal sentiment analysis with image-text interaction network

More and more users are getting used to posting images and text on social networks to share their emotions or opinions. Accordingly, multimodal sentiment analysis has become a research topic of increasing interest in recent years. Typically, there exist affective regions that evoke human sentiment in an image, which are usually manifested by corresponding words in peoples comments. Similarly, people also tend to portray the affective regions of an image when composing image descriptions. As a result, the relationship between image affective regions and the associated text is of great significance for multimodal sentiment analysis. However, most of the existing multimodal sentiment analysis approaches simply concatenate features from image and text, which could not fully explore the interaction between them, leading to suboptimal results. Motivated by this observation, we propose a new image-text interaction network (ITIN) to investigate the relationship between affective image regions and text for multimodal sentiment analysis. Specifically, we introduce a cross-modal alignment module to capture region-word correspondence, based on which multimodal features are fused through an adaptive cross-modal gating module. Moreover, considering the complementary role of context information on sentiment analysis, we integrate the individual-modal contextual feature representations for achieving more reliable prediction. Extensive experimental results and comparisons on public datasets demonstrate that the proposed model is superior to the state-of-the-art methods

Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD) or high-density (HD) SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE) or haplotype-averaged Shannon entropy (HASE) and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with more computing time. Nevertheless, the differences diminished when \u3e5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced) or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with \u3e3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus population. The utility of this MOLO algorithm was also demonstrated in a real application, in which a 6K SNP panel was optimized conditional on 5,260 obligatory SNP selected based on SNP-trait association in U.S. Holstein animals. With this MOLO algorithm, both imputation error rate and genomic prediction error rate were minimal

Eight RGS and RGS-like Proteins Orchestrate Growth, Differentiation, and Pathogenicity of Magnaporthe oryzae

A previous study identified MoRgs1 as an RGS protein that negative regulates G-protein signaling to control developmental processes such as conidiation and appressorium formation in Magnaporthe oryzae. Here, we characterized additional seven RGS and RGS-like proteins (MoRgs2 through MoRgs8). We found that MoRgs1 and MoRgs4 positively regulate surface hydrophobicity, conidiation, and mating. Indifference to MoRgs1, MoRgs4 has a role in regulating laccase and peroxidase activities. MoRgs1, MoRgs2, MoRgs3, MoRgs4, MoRgs6, and MoRgs7 are important for germ tube growth and appressorium formation. Interestingly, MoRgs7 and MoRgs8 exhibit a unique domain structure in which the RGS domain is linked to a seven-transmembrane motif, a hallmark of G-protein coupled receptors (GPCRs). We have also shown that MoRgs1 regulates mating through negative regulation of Gα MoMagB and is involved in the maintenance of cell wall integrity. While all proteins appear to be involved in the control of intracellular cAMP levels, only MoRgs1, MoRgs3, MoRgs4, and MoRgs7 are required for full virulence. Taking together, in addition to MoRgs1 functions as a prominent RGS protein in M. oryzae, MoRgs4 and other RGS and RGS-like proteins are also involved in a complex process governing asexual/sexual development, appressorium formation, and pathogenicity

Expenditures for the care of HIV-infected patients in rural areas in China's antiretroviral therapy programs

<p>Abstract</p> <p>Background</p> <p>The Chinese government has provided health services to those infected by the human immunodeficiency virus (HIV) under the acquired immunodeficiency syndrome (AIDS) care policy since 2003. Detailed research on the actual expenditures and costs for providing care to patients with AIDS is needed for future financial planning of AIDS health care services and possible reform of HIV/AIDS-related policy. The purpose of the current study was to determine the actual expenditures and factors influencing costs for untreated AIDS patients in a rural area of China after initiating highly active antiretroviral therapy (HAART) under the national Free Care Program (China CARES).</p> <p>Methods</p> <p>A retrospective cohort study was conducted in Yunnan and Shanxi Provinces, where HAART and all medical care are provided free to HIV-positive patients. Health expenditures and costs in the first treatment year were collected from medical records and prescriptions at local hospitals between January and June 2007. Multivariate linear regression was used to determine the factors associated with the actual expenditures in the first antiretroviral (ARV) treatment year.</p> <p>Results</p> <p>Five ARV regimens are commonly used in China CARES: zidovudine (AZT) + lamivudine (3TC) + nevirapine (NVP), stavudine (D4T) + 3TC + efavirenz (EFV), D4T + 3TC + NVP, didanosine (DDI) + 3TC + NVP and combivir + EFV. The mean annual expenditure per person for ARV medications was US$2,242 (US$1 = 7 Chinese Yuan (CNY)) among 276 participants. The total costs for treating all adverse drug events (ADEs) and opportunistic infections (OIs) were US$29,703 and US$23,031, respectively. The expenses for treatment of peripheral neuritis and cytomegalovirus (CMV) infections were the highest among those patients with ADEs and OIs, respectively. On the basis of multivariate linear regression, CD4 cell counts (100-199 cells/μL versus <100 cells/μL, <it>P </it>= 0.02; and ≥200 cells/μL versus <100 cells/μL, <it>P </it>< 0.004), residence in Mangshi County (<it>P </it>< 0.0001), ADEs (<it>P </it>= 0.04) and OIs (<it>P </it>= 0.02) were significantly associated with total expenditures in the first ARV treatment year.</p> <p>Conclusions</p> <p>This is the first study to determine the actual costs of HIV treatment in rural areas of China. Costs for ARV drugs represented the major portion of HIV medical expenditures. Initiating HAART in patients with higher CD4 cell count levels is likely to reduce treatment expenses for ADEs and OIs in patients with AIDS.</p