Inspired by the coupling phenomenon in biological system, the gray cast iron specimens with the bionic coupling stripes were fabricated by laser. The effects of laser processing parameters on the dimension and hardness of bionic coupling units were investigated and discussed. Regression-orthogonal design was adopted in this study to develop the mathematical models, which showed the clear quantitative relationship between the laser processing parameters and the geometrical dimension and hardness of bionic coupling units. The models developed were checked for their significance by using F-test. Both the significant test and the verification test results demonstrated that the mathematical models developed were accurate and reliable in the experimental range. Based on the models, the maximum diameter, penetration depth and the maximum average hardness of bionic coupling units of gray cast iron were obtained. The diameter, penetration depth and average hardness of bionic coupling stripes under different laser processing parameters could be predicted to meet the requirement of bionic manufacturing by the mathematical equations. And the adjustment of laser processing parameters was an effective method to improve the fabrication quality of bionic coupling units. (C) 2016 Laser Institute of America.

Despite considerable research on the environmental impacts of nanomaterials, we know little about how they influence interactions between species. Here, we investigated the acute (12 d) and chronic (64 d) toxicities of cerium oxide nanoparticles (CeO2 NPs) and bulk particles (0-200 mg/L) to three ciliated protist species (Loxocephalus sp., Paramecium aurelia, and Tetrahymena pyriformis) in single-, bi-, and multispecies microcosms. The results show that CeO2 NPs strongly affected the interactions between ciliated protozoan species. When exposed to the highest CeO2 NPs (200 mg/L), the intrinsic growth rates of Loxocephalus and Paramecium were significantly decreased by 18.87% and 88.27%, respectively, while their carrying capacities declined by more than 90%. However, CeO2 NP exposure made it difficult to predict outcomes of interspecific competition between species. At higher NP exposure (100 and 200 mg/L), competition led to the extinction of both species in the Loxocephalus and Paramecium microcosms that survived in the absence of competitors or CeO2 NPs. Further, the presence of potential competitors improved the survival of Loxocephalus to hundreds of individuals per milliliter in microcosms with Tetrahymena where Loxocephalus would otherwise not be able to tolerate high levels of NP exposure. This result could be attributed to weakened NP adsorption on the cell surface due to competitor-caused reduction of NP surface charge (from 18.52 to 25.17 mV) and intensified NP aggregation via phagocytosis of NPs by ciliate cells. Our results emphasize the need to explicitly consider species interactions for a more comprehensive understanding of the ecological consequences of NP exposure.

Most commonly used adaptive algorithms for univariate real valued function approximation and global minimization lack theoretical guarantees. Our new locally adaptive algorithms are guaranteed to provide answers that satisfy a user-specified absolute error tolerance for a cone, C, of non-spiky input functions in the Sobolev space W-2,W- infinity [a, b]. Our algorithms automatically determine where to sample the function-sampling more densely where the second derivative is larger. The computational cost of our algorithm for approximating a univariate function f on a bounded interval with L-infinity-error no greater than epsilon is phi(root||f ''|| 1/2 /epsilon) as epsilon -> 0. This is the same order as that of the best function approximation algorithm for functions in C. The computational cost of our global minimization algorithm is of the same order and the cost can be substantially less if f significantly exceeds its minimum over much of the domain. Our Guaranteed Automatic Integration Library (GAIL) contains these new algorithms. We provide numerical experiments to illustrate their superior performance. (C) 2016 Elsevier Inc. All rights reserved.

Sketching provides an intuitive user interface for communicating free form shapes. While human observers can easily envision the shapes they intend to communicate, replicating this process algorithmically requires resolving numerous ambiguities. Existing sketch-based modeling methods resolve these ambiguities by either relying on expensive user annotations or by restricting the modeled shapes to specific narrow categories. We present an approach for modeling generic freeform 3D surfaces from sparse, expressive 2D sketches that overcomes both limitations by incorporating convolution neural networks (CNN) into the sketch processing workflow. Given a 2D sketch of a 3D surface, we use CNNs to infer the depth and normal maps representing the surface. To combat ambiguity we introduce an intermediate CNN layer that models the dense curvature direction, or flow, field of the surface, and produce an additional output confidence map along with depth and normal. The flow field guides our subsequent surface reconstruction for improved regularity; the confidence map trained unsupervised measures ambiguity and provides a robust estimator for data fitting. To reduce ambiguities in input sketches users can refine their input by providing optional depth values at sparse points and curvature hints for strokes. Our CNN is trained on a large dataset generated by rendering sketches of various 3D shapes using non-photo-realistic line rendering (NPR) method that mimics human sketching of free-form shapes. We use the CNN model to process both single- and multi-view sketches. Using our multi-view framework users progressively complete the shape by sketching in different views, generating complete closed shapes. For each new view, the modeling is assisted by partial sketches and depth cues provided by surfaces generated in earlier views. The partial surfaces are fused into a complete shape using predicted confidence levels as weights. We validate our approach, compare it with previous methods and alternative structures, and evaluate its performance with various modeling tasks. The results demonstrate our method is a new approach for efficiently modeling freeform shapes with succinct but expressive 2D sketches.

We present AppGen, an interactive system for modeling materials from a single image. Given a texture image of a nearly planar surface lit with directional lighting, our system models the detailed spatially-varying reflectance properties (diffuse, specular and roughness) and surface normal variations with minimal user interaction. We ask users to indicate global shading and reflectance information by roughly marking the image with a few user strokes, while our system assigns reflectance properties and normals to each pixel. We first interactively decompose the input image into the product of a diffuse albedo map and a shading map. A two-scale normal reconstruction algorithm is then introduced to recover the normal variations from the shading map and preserve the geometric features at different scales. We finally assign the specular parameters to each pixel guided by user strokes and the diffuse albedo. Our system generates convincing results within minutes of interaction and works well for a variety of material types that exhibit different reflectance and normal variations, including natural surfaces and man-made ones.

Waste is wicked because of its inextricable mix of social, economic, and environmental attributes. This paper presents the unexpected explosion of a "waste city", Dongxiaokou, on the northern fringe of Beijing in the 2000s and its recent crash due to urban expansion. These events occurred within the background of the municipality's efforts to remake the waste/recycling space into an "urban circular economic system". We illustrate the distressing challenge of waste as it is gradually exposed to urban governance in China. Our findings show that waste can be wicked because of the limits of its problem definition, which focuses on the environment and resources, but excludes the migrant scavengers from the local citizenry regardless their efforts for inclusion by the city. This limitation of the definition of the problem leads to conflicting values on waste and recycling between various stakeholders who are involved when the system needs to be upgraded. Conclusions suggest collaborative initiatives at the community level to build an inclusive space for recycling activities in cities in China. (C) 2015 Elsevier B.V. All rights reserved.

Shot peen forming is widely used in aerospace industry to form the thin components with complex contour by introducing compressive stresses. The compressive stresses are hypothetically introduced into a perfectly constrained target in conventional researches. However, the desired curvatures are obtained incrementally in actual forming process. In this paper, a stepping numerical model is proposed to study the effect of boundary constraints on the peening stresses and resulting curvatures. First, axisymmetric simulations are carried out to determine optimal mesh sizes. Then, simulations with a three-dimensional target subjected to 65 shot impacts step by step are carried out with applying different intermittently released boundary constraints. It is found that the boundary constraints can significantly influence the evolutions of peening stress and curvature. Finally, comparison of numerical and experimental results shows that actually obtained peen forming curvatures lie between the numerical results with perfectly constraints and that with relatively loose constrains.

Aims/hypothesis Sirtuin 6 (SIRT6) has been implicated in ageing, DNA repair and metabolism; however, its function in pancreatic beta cells is unclear. The aim of this study is to elucidate the role of SIRT6 in pancreatic beta cells.Methods To investigate the function of SIRT6 in pancreatic beta cells, we performed Sirt6 gene knockdown in MIN6 cells and generated pancreatic- and beta cell-specific Sirt6 knockout mice. Islet morphology and glucose-stimulated insulin secretion (GSIS) were analysed. Glycolysis and oxygen consumption rates in SIRT6-deficient beta cells were measured. Cytosolic calcium was monitored using the Fura-2-AM fluorescent probe (Invitrogen, Grand Island, NY, USA). Mitochondria were analysed by immunoblots and electron microscopy.Results Sirt6 knockdown in MIN6 beta cells led to a significant decrease in GSIS. Pancreatic beta cell Sirt6 knockout mice showed a similar to 50% decrease in GSIS. The knockout mouse islets had lower ATP levels compared with the wild-type controls. Mitochondrial oxygen consumption rates were significantly decreased in the SIRT6-deficient beta cells. Cytosolic calcium dynamics in response to glucose or potassium chloride were attenuated in the Sirt6 knockout islets. Numbers of damaged mitochondria were increased and mitochondrial complex levels were decreased in the SIRT6-deficient islets.Conclusions/interpretation These data suggest that SIRT6 is important for GSIS from pancreatic beta cells and activation of SIRT6 may be useful to improve insulin secretion in diabetes.

The degradation kinetics and micro-scale structure change of microcrystalline cellulose during anaerobic biodegradation were investigated. A modified Logistic model was established to properly describe the kinetics, which showed good fitness and wide applicability for cellulose degradation. A maximum degradation rate of 0.14 g L-1 h(-1) was achieved after cultivating for 51.5 h. This result was in good agreement with the scanning electron microscope and X-ray diffraction analysis. Channels of 400-500 nm size started to occur on the crystalline surface of cellulose at around the inflexion time. Accordingly, the crystallinity significantly decreased at this point, indicating a degradation of the crystalline structure zones by anaerobic bacteria. This study offers direct morphological evidence and quantitative analysis of the biodegradation process of cellulose, and is beneficial to a better understanding of the cellulose degradation mechanism. (C) 2011 Elsevier Ltd. All rights reserved.