Perception Driven Texture Generation

This paper investigates a novel task of generating texture images from perceptual descriptions. Previous work on texture generation focused on either synthesis from examples or generation from procedural models. Generating textures from perceptual attributes have not been well studied yet. Meanwhile, perceptual attributes, such as directionality, regularity and roughness are important factors for human observers to describe a texture. In this paper, we propose a joint deep network model that combines adversarial training and perceptual feature regression for texture generation, while only random noise and user-defined perceptual attributes are required as input. In this model, a preliminary trained convolutional neural network is essentially integrated with the adversarial framework, which can drive the generated textures to possess given perceptual attributes. An important aspect of the proposed model is that, if we change one of the input perceptual features, the corresponding appearance of the generated textures will also be changed. We design several experiments to validate the effectiveness of the proposed method. The results show that the proposed method can produce high quality texture images with desired perceptual properties.Comment: 7 pages, 4 figures, icme201

Research progress on GlnR-mediated regulation in Actinomycetes

This review constitutes a summary of current knowledge on GlnR, a global regulator, that assumes a critical function in the regulation of nitrogen metabolism of Actinomycetes. In cross-regulation with other regulators, GlnR was also shown to play a role in the regulation of carbon and phosphate metabolisms as well as of secondary metabolism. A description of the structure of the GlnR protein and of its binding sites in various genes promoters regions is also provided. This review thus provides a global understanding of the critical function played by GlnR in the regulation of primary and secondary metabolism in Actinomycetes

Phase Changes in the Evolution of the IPv4 and IPv6 AS-Level Internet Topologies

In this paper we investigate the evolution of the IPv4 and IPv6 Internet topologies at the autonomous system (AS) level over a long period of time.We provide abundant empirical evidence that there is a phase transition in the growth trend of the two networks. For the IPv4 network, the phase change occurred in 2001. Before then the network's size grew exponentially, and thereafter it followed a linear growth. Changes are also observed around the same time for the maximum node degree, the average node degree and the average shortest path length. For the IPv6 network, the phase change occurred in late 2006. It is notable that the observed phase transitions in the two networks are different, for example the size of IPv6 network initially grew linearly and then shifted to an exponential growth. Our results show that following decades of rapid expansion up to the beginning of this century, the IPv4 network has now evolved into a mature, steady stage characterised by a relatively slow growth with a stable network structure; whereas the IPv6 network, after a slow startup process, has just taken off to a full speed growth. We also provide insight into the possible impact of IPv6-over-IPv4 tunneling deployment scheme on the evolution of the IPv6 network. The Internet topology generators so far are based on an inexplicit assumption that the evolution of Internet follows non-changing dynamic mechanisms. This assumption, however, is invalidated by our results.Our work reveals insights into the Internet evolution and provides inputs to future AS-Level Internet models.Comment: 12 pages, 21 figures; G. Zhang et al.,Phase changes in the evolution of the IPv4 and IPv6 AS-Level Internet topologies, Comput. Commun. (2010

Hepatitis B virus inhibition in mice by lentiviral vector mediated short hairpin RNA

<p>Abstract</p> <p>Background</p> <p>Chronic hepatitis B virus (HBV) infection is an important cause of cirrhosis and hepatocellular carcinoma. The major challenges for current therapies are the low efficacy of current drugs and the occurrence of drug resistant HBV mutations. RNA interference (RNAi) of virus-specific genes offers the possibility of developing a new anti-HBV therapy. Recent reports have shown that lentiviral vectors based on HIV-1 are promising gene delivery vehicles due to their ability to integrate transgenes into non-dividing cells. Herein, a lentivirus-based RNAi system was developed to drive expression and delivery of HBV-specific short hairpin RNA (shRNA) in a mouse model for HBV replication.</p> <p>Methods</p> <p>Hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) in the sera of the mice were analyzed by quantitative sandwich enzyme linked immunosorbent assay (ELISA) technique, hepatitis B core antigen (HBcAg) and HBsAg in the livers of the mice were detected by immunohistochemical assay, HBV DNA and HBV mRNA were measured by fluorogenic quantitative polymerase chain reaction (FQ-PCR) and quantitative real-time PCR respectively.</p> <p>Results</p> <p>Co-injection of HBV plasmids together with the lentivirus targeting HBV shRNA induced an RNAi response. Secreted HBsAg was reduced by 89% in mouse serum, and HBeAg was also significantly inhibited, immunohistochemical detection of HBcAg or HBsAg in the liver tissues also revealed substantial reduction. Lentiviral mediated shRNA caused a significant suppression in the levels of viral mRNA and DNA synthesis compared to the control group.</p> <p>Conclusion</p> <p>Lentivirus-based RNAi can be used to suppress HBV replication in vivo, it might become a potential therapeutic strategy for treating HBV and other viral infections.</p

Lightweight conductive graphene/thermoplastic polyurethane foams with ultrahigh compressibility for piezoresistive sensing

Lightweight conductive porous graphene/thermoplastic polyurethane (TPU) foams with ultrahigh compressibility were successfully fabricated by using the thermal induced phase separation (TISP) technique. The density and porosity of the foams were calculated to be about 0.11 g cm−3 and 90% owing to the porous structure. Compared with pure TPU foams, the addition of graphene could effectively increase the thickness of the cell wall and hinder the formation of small holes, leading to a robust porous structure with excellent compression property. Meanwhile, the cell walls with small holes and a dendritic structure were observed due to the flexibility of graphene, endowing the foam with special positive piezoresistive behaviors and peculiar response patterns with a deflection point during the cyclic compression. This could effectively enhance the identifiability of external compression strain when used as piezoresistive sensors. In addition, larger compression sensitivity was achieved at a higher compression rate. Due to high porosity and good elasticity of TPU, the conductive foams demonstrated good compressibility and stable piezoresistive sensing signals at a strain of up to 90%. During the cyclic piezoresistive sensing test under different compression strains, the conductive foam exhibited good recoverability and reproducibility after the stabilization of cyclic loading. All these suggest that the fabricated conductive foam possesses great potential to be used as lightweight, flexible, highly sensitive, and stable piezoresistive sensors

Image-guided prostate biopsy robots: A review

At present, the incidence of prostate cancer (PCa) in men is increasing year by year. So, the early diagnosis of PCa is of great significance. Transrectal ultrasonography (TRUS)-guided biopsy is a common method for diagnosing PCa. The biopsy process is performed manually by urologists but the diagnostic rate is only 20%–30% and its reliability and accuracy can no longer meet clinical needs. The image-guided prostate biopsy robot has the advantages of a high degree of automation, does not rely on the skills and experience of operators, reduces the work intensity and operation time of urologists and so on. Capable of delivering biopsy needles to pre-defined biopsy locations with minimal needle placement errors, it makes up for the shortcomings of traditional free-hand biopsy and improves the reliability and accuracy of biopsy. The integration of medical imaging technology and the robotic system is an important means for accurate tumor location, biopsy puncture path planning and visualization. This paper mainly reviews image-guided prostate biopsy robots. According to the existing literature, guidance modalities are divided into magnetic resonance imaging (MRI), ultrasound (US) and fusion image. First, the robot structure research by different guided methods is the main line and the actuators and material research of these guided modalities is the auxiliary line to introduce and compare. Second, the robot image-guided localization technology is discussed. Finally, the image-guided prostate biopsy robot is summarized and suggestions for future development are provided

Progressive damage numerical modelling and simulation of aircraft composite bolted joints bearing response

Finite element numerical progressive damage modelling and simulations applied to the strength prediction of airframe bolted joints on composite laminates can lead to shorter and more efficient product cycles in terms of design, analysis and certification, while benefiting the economic manufacturing of composite structures. In the study herein, experimental bolted joint bearing tests were carried out to study the strength and failure modes of fastened composite plates under static tensile loads. The experimental results were subsequently benchmarked against various progressive damage numerical modelling simulations where the effects of different failure criteria, damage variables and subroutines were considered. Evidence was produced that indicated that both the accuracy of the simulation results and the speed of calculation were affected by the choice of user input and numerical scheme