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In this research study, the fracture strength of flat 10 mm thick annealed glass sheets having an abrasive water-jet cut surface and bearing against a transparent interface material is experimentally investigated. The transparent interface material is necessary to provide axial-compressive force continuity in modular compression-dominant all- glass shell structures. A series of short glass columns were tested in axial compression under a variety of load cases, which included cyclic, creep, and monotonic-to-fracture loading. A target glass fracture bearing stress of 36.6 MPa is identified and represents an upper bound bearing stress for annealed glass compression members failing in a flexural buckling mode. The study concludes the transparent thermoplastic material, known as Surlyn, was able to achieve a fracture strength that exceeds the target value and that the fracture strength is not affected by cyclic or creep loading. Consequently, column-related failure limit states will occur before glass fracture is associated with interface bearing. Glass fracture occurs in Type-I mode, reflecting the presence of interface tensile stress. Furthermore, the monotonic bearing stiffness in the service range of 5 to 15 MPa is increased by 20 % and 16 % for samples subjected to cyclic and creep loading, respectively, relative to monotonic-only samples. 

Multi-layer spatial structures usually take considerable external loads with a small material usage at all scales. Polyhedral graphic statics (PGS) provides a method to design multi-layer funicular polyhedral structures, and the structural forms are usually materialized as space frames. Our previous research shows that the intrinsic planarity of the polyhedral geometries can be harnessed for efficient fabrication and construction processes using flat-sheet materials. Sheet-based structures are advantageous over conventional space frame systems because sheets can provide more load paths and constrain the kinematic degrees of freedom of the nodes. Therefore, they are more capable of taking a wider variety of load cases compared to space frames. Moreover, sheet materials can be fabricated into complex shapes using CNC milling, laser cutting, water jet cutting, and CNC bending techniques. However, not all sheets are necessary as long as the load paths are preserved and the system does not have kinematic degrees of freedom. To find an efficient set of faces that satisfies the requirements, this paper first incorporates and adapts the matrix analysis method to calculate the kinematic degrees of freedom for sheet-based structures. Then, an iterative algorithm is devised to help find a reduced set of faces with zero kinematic degrees of freedom. To attest to the advantages of this method over bar-node construction, a comparative study is carried out using finite element analysis. The results show that, with the same material usage, the sheet-based system has improved performance than the framework system under a range of loading scenarios. 

Abstract Long-duration GRB 200829A was detected by Fermi-GBM and Swift-BAT/XRT, and then rapidly observed by other ground-based telescopes. It has a weak γ -ray emission in the very early phase and is followed by a bright spiky γ -ray emission pulse. The radiation spectrum of the very early emission is best fitted by a power-law function with index ∼−1.7. However, the bright spiky γ -ray pulse, especially the time around the peak, exhibits a distinct two-component radiation spectrum, i.e., Band function combined with a blackbody radiation spectrum. We infer the photospheric properties and reveal a medium magnetization at a photospheric position by adopting the initial size of the outflow as r 0 = 10 9 cm. It implies that the Band component in this pulse may be formed during the dissipation of the magnetic field. The power-law radiation spectra found in the very early prompt emission may imply the external-shock origination of this phase. Then, we perform the Markov Chain Monte Carlo method fitting on the light curves of this burst, where the jet corresponding to the γ -ray pulse at around 20 s is used to refresh the external shock. It is shown that the light curves of the very early phase and X-ray afterglow after 40 s, involving the X-ray bump at around 100 s, can be well modeled in the external-shock scenario. For the obtained initial outflow, we estimate the minimum magnetization factor of the jet based on the fact that the photospheric emission of this jet is missed in the very early phase. 

We will demonstrate a prototype query-processing engine, which utilizes correlations among predicates to accelerate machine learning (ML) inference queries on unstructured data. Expensive operators such as feature extractors and classifiers are deployed as user-defined functions (UDFs), which are not penetrable by classic query optimization techniques such as predicate push-down. Recent optimization schemes (e.g., Probabilistic Predicates or PP) build a cheap proxy model for each predicate offline, and inject proxy models in the front of expensive ML UDFs under the independence assumption in queries. Input records that do not satisfy query predicates are filtered early by proxy models to bypass ML UDFs. But enforcing the independence assumption may result in sub-optimal plans. We use correlative proxy models to better exploit predicate correlations and accelerate ML queries. We will demonstrate our query optimizer called CORE, which builds proxy models online, allocates parameters to each model, and reorders them. We will also show end-to-end query processing with or without proxy models. 

Multi-layer spatial structures usually take considerable external loads with very limited material usage at all scales, and Polyhedral Graphic Statics (PGS) provides a method to design multi-layer funicular polyhedral structures. The structural forms usually materialized as space frames. Our previous research shows that the intrinsic planarity of the polyhedral geometries can be harnessed for efficient fabrication and construction processes using flat-sheet materials. Sheet-based structures are advantageous over the conventional space frame systems because sheets can provide more load paths and constrain the kinematic degrees of freedom of the nodes. Therefore, they can take a wider range of load compared to space frames. Moreover, sheet materials can be fabricated to complex shapes using CNC milling, laser cutting, water jet cutting, and CNC bending techniques. However, not all sheets are necessary as long as the load paths are preserved, and the system does not have kinematic degrees of freedom. To find a reduced set of faces that satisfies the requirements, this paper incorporates and adapts the matrix analysis method to calculate the kinematic degree of freedom of sheet-based structure. Built upon this, an iterative algorithm is devised to help find the reduced set of faces with zero kinematic degree of freedom. To attest the advantage of this method over bar-node construction, a comparative study is carried out using finite element analysis. The result shows that, with the same material usage, the sheet-based system has improved performance than the framework system under a wide range of loading scenarios. 

We consider accelerating machine learning (ML) inference queries on unstructured datasets. Expensive operators such as feature extractors and classifiers are deployed as user-defined functions (UDFs), which are not penetrable with classic query optimization techniques such as predicate push-down. Recent optimization schemes (e.g., Probabilistic Predicates or PP) assume independence among the query predicates, build a proxy model for each predicate offline, and rewrite a new query by injecting these cheap proxy models in the front of the expensive ML UDFs. In such a manner, unlikely inputs that do not satisfy query predicates are filtered early to bypass the ML UDFs. We show that enforcing the independence assumption in this context may result in sub-optimal plans. In this paper, we propose CORE, a query optimizer that better exploits the predicate correlations and accelerates ML inference queries. Our solution builds the proxy models online for a new query and leverages a branch-and-bound search process to reduce the building costs. Results on three real-world text, image and video datasets show that CORE improves the query throughput by up to 63% compared to PP and up to 80% compared to running the queries as it is. 

Abstract The goal of this study is to develop a new computed tomography (CT) image reconstruction method, aiming at improving the quality of the reconstructed images of existing methods while reducing computational costs. Existing CT reconstruction is modeled by pixel-based piecewise constant approximations of the integral equation that describes the CT projection data acquisition process. Using these approximations imposes a bottleneck model error and results in a discrete system of a large size. We propose to develop a content-adaptive unstructured grid (CAUG) based regularized CT reconstruction method to address these issues. Specifically, we design a CAUG of the image domain to sparsely represent the underlying image, and introduce a CAUG-based piecewise linear approximation of the integral equation by employing a collocation method. We further apply a regularization defined on the CAUG for the resulting ill-posed linear system, which may lead to a sparse linear representation for the underlying solution. The regularized CT reconstruction is formulated as a convex optimization problem, whose objective function consists of a weighted least square norm based fidelity term, a regularization term and a constraint term. Here, the corresponding weighted matrix is derived from the simultaneous algebraic reconstruction technique (SART). We then develop a SART-type preconditioned fixed-point proximity algorithm to solve the optimization problem. Convergence analysis is provided for the resulting iterative algorithm. Numerical experiments demonstrate the superiority of the proposed method over several existing methods in terms of both suppressing noise and reducing computational costs. These methods include the SART without regularization and with the quadratic regularization, the traditional total variation (TV) regularized reconstruction method and the TV superiorized conjugate gradient method on the pixel grid.