Adaptive synthesis of distance fields

We address the computational resource requirements of 3D example-based synthesis with an adaptive synthesis technique that uses a tree-based synthesis map. A signed-distance field (SDF) is determined for the 3D exemplars, and then new models can be synthesized as SDFs by neighborhood matching. Unlike voxel synthesis approach, our input is posed in the real domain to preserve maximum detail. In comparison to straightforward extensions to the existing volume texture synthesis approach, we made several improvements in terms of memory requirements, computation times, and synthesis quality. The inherent parallelism in this method makes it suitable for a multicore CPU. Results show that computation times and memory requirements are very much reduced, and large synthesized scenes exhibit fine details which mimic the exemplars.     

An intrinsic semantic framework for recognizing image objects

The paper proposes a new approach to find semantic meanings in visual object class structure, in line with the Gestalt laws of proximity. Micro level semantic structures are formed by line segments (arcs also approximated into line segments based on pixel deviation threshold) which are in close proximity. These structures are hierarchically combined till a semantic label can be assigned. The algorithm extracts semantic groups, their inter-relations and represents these using a graph. Invariant geometrical properties of the groups and relations are used as vertex and edge labels. A graph model captures the inter class variability by analyzing the repetitiveness of structures and relations and uses it as a weighting factor for classification. The algorithm has been tested on a standard benchmark database and compared with existing approaches.     

Generalized extreme learning machine acting on a metric space

Functional data learning is an extension of traditional data learning, that is, learning the data chosen from the Euclidean space ${\mathbb{R}^{n}}$ to a metric space. This paper focuses on the functional data learning with generalized single-hidden layer feedforward neural networks (GSLFNs) acting on some metric spaces. In addition, three learning algorithms, named Hilbert parallel overrelaxation backpropagation (H-PORBP) algorithm, ν-generalized support vector regression (ν-GSVR) and generalized extreme learning machine (G-ELM) are proposed to train the GSLFNs acting on some metric spaces. The experimental results on some metric spaces indicate that GELM with additive/RBF hidden-nodes has a faster learning speed, a better accuracy, and a better stability than HPORBP algorithm and ν-GSVR for training the functional data. The idea of GELM can be used to extend those improved extreme learning machines (ELMs) that act on the Euclidean space ${\mathbb{R}^{n}, }$ such as online sequential ELM, incremental ELM, pruning ELM and so on, to some metric spaces.     

The α- to β-Si3N4 transformation in the presence of liquid silicon

The compacts consisted of , -Si₃N₄ and free silicon are heat treated in the range 1650° C to 1750° C in an argon atmosphere in order to observe the following behaviours; the to phase transformation and variations of the microstructure during heat treatment in silicon nitride. For the microstructural observation of the heat treated specimens, the same grains in the polished surface were investigated before and after eliminating the retained silicon by etching. The to phase transformation, in this case, occurs via silicon melts irrespective of added -Si₃N₄. Both and phases are soluted and precipitated into molten silicon and their morphology are changed from an equiaxed shape to prismatic one. Although elongated grains are precipitated at low temperature or in the early stage of heat treatment, fine precipitated grains are mainly observed with increasing heat treating temperature.     

Dielectric properties and microstructural behaviour of B-site calcium-doped barium titanate ceramics

Dielectric properties and microstructural behaviour of Ba_1–x Sr _x Ti_1–y Ca _y O_3–y ceramics, where strontium and calcium were doped on the barium and titanium sites, respectively, within the range 0x0.24 and 0y0.05, were investigated. Calcium addition decreased the tetragonality,c/a, increased the unit cell volume, and lowered the Curie temperature, which were all attributed to the occupancy of Ca²⁺ ions on titanium sites. When sintered at a low oxygen partial pressure of 10^–9 MPa, a resistivity higher than 10¹¹ cm was maintained for the formulations containing B-site calcium substitution more than 0.5 mol %. With increasing the amount of calcium addition, the Curie peak was depressed and completely broadened for the compositions with calcium addition more than 3 mol %, where the average grain size was smaller than 1 m. Co-firing with nickel electrodes in a reducing atmosphere also depressed the Curie peak and inhibited the grain growth due to the diffusion of nickel into the dielectrics.     

利用CFD技术研究四边形通道内的流场

了解认知隧道内的流体力学的特点对于隧道火灾的研究和隧道安全建设有着非常大的意义。为了对隧道火灾的特点进行研究,我们使用商用CFD程序STAR-CD对速度场和压力分布进行了数值模拟。模拟过程中在同一入口位置的情况下改变四个出口位置,出口位置与模具高度的数值对别分别为L/H=0,0.375,0.75,1.125。同时还介绍了对于火灾救援和人员疏散的有效措施。     

The diffusion and solubility of oxygen in solid nickel

Solid-state electrochemical measurements using various experimental procedures were made with the double cell: $$ Ni + NiO|ZrO_2 + Y_2 O_3 |Ni + \underline O |ZrO_2 + Y_2 O_3 |Ni + NiO $$ to determine the diffusivity and thermodynamic functions of oxygen dissolved in solid nickel. Non-steady state diffusion of oxygen in the specimen was caused by applying a preselected potential between the reference and specimen electrodes and was monitored by measuring time-dependent potentials and/or currents. The following results were obtained for the diffusivity of oxygen and the solubility of oxygen in nickel in equilibrium with NiO: $$D{\text{ = 4}}{\text{.9 }} \times {\text{ 10}}^{{\text{ - 2}}} {\text{ exp}}\left( {{\text{ - }}\frac{{{\text{164 kJ/mole}}}}{{{\text{R}}T}}} \right){\text{cm}}^{\text{2}} /{\text{sec (850 to 1400 }}{}^{\text{o}}{\text{C)}}$$ $$C_{\text{O}}^s {\text{ = 8}}{\text{.3 exp}}\left( { - \frac{{55{\text{kJ/mole}}}}{{{\text{R}}T}}} \right){\text{at}}{\text{. pct (800 to 1000 }}{}^{\text{o}}{\text{C)}}$$ The thermodynamic and transport behaviors of oxygen in solid nickel were fairly well described by a simple quasi-regular model and an interstitial diffusion model, respectively.     

Human DDX3X Unwinds Japanese Encephalitis and Zika Viral 5′ Terminal Regions

Flavivirus genus includes many deadly viruses such as the Japanese encephalitis virus (JEV) and Zika virus (ZIKV). The 5′ terminal regions (TR) of flaviviruses interact with human proteins and such interactions are critical for viral replication. One of the human proteins identified to interact with the 5′ TR of JEV is the DEAD-box helicase, DDX3X. In this study, we in vitro transcribed the 5′ TR of JEV and demonstrated its direct interaction with recombinant DDX3X (K_d of 1.66 ± 0.21 µM) using microscale thermophoresis (MST). Due to the proposed structural similarities of 5′ and 3′ TRs of flaviviruses, we investigated if the ZIKV 5′ TR could also interact with human DDX3X. Our MST studies suggested that DDX3X recognizes ZIKV 5′ TR with a K_d of 7.05 ± 0.75 µM. Next, we performed helicase assays that suggested that the binding of DDX3X leads to the unwinding of JEV and ZIKV 5′ TRs. Overall, our data indicate, for the first time, that DDX3X can directly bind and unwind in vitro transcribed flaviviral TRs. In summary, our work indicates that DDX3X could be further explored as a therapeutic target to inhibit Flaviviral replication     

CRISPR/Cas9-Mediated Generation of Pathogen-Resistant Tomato against Tomato Yellow Leaf Curl Virus and Powdery Mildew

Tomato is one of the major vegetable crops consumed worldwide. Tomato yellow leaf curl virus (TYLCV) and fungal Oidium sp. are devastating pathogens causing yellow leaf curl disease and powdery mildew. Such viral and fungal pathogens reduce tomato crop yields and cause substantial economic losses every year. Several commercial tomato varieties include Ty-5 (SlPelo) and Mildew resistance locus o 1 (SlMlo1) locus that carries the susceptibility (S-gene) factors for TYLCV and powdery mildew, respectively. The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) is a valuable genome editing tool to develop disease-resistant crop varieties. In this regard, targeting susceptibility factors encoded by the host plant genome instead of the viral genome is a promising approach to achieve pathogen resistance without the need for stable inheritance of CRISPR components. In this study, the CRISPR/Cas9 system was employed to target the SlPelo and SlMlo1 for trait introgression in elite tomato cultivar BN-86 to confer host-mediated immunity against pathogens. SlPelo-knockout lines were successfully generated, carrying the biallelic indel mutations. The pathogen resistance assays in SlPelo mutant lines confirmed the suppressed accumulation of TYLCV and restricted the spread to non-inoculated plant parts. Generated knockout lines for the SlMlo1 showed complete resistance to powdery mildew fungus. Overall, our results demonstrate the efficiency of the CRISPR/Cas9 system to introduce targeted mutagenesis for the rapid development of pathogen-resistant varieties in tomato.