Apparatus and process for freeform fabrication of composite reinforcement preforms

A solid freeform fabrication process and apparatus for making a three-dimensional reinforcement shape. The process comprises the steps of (1) operating a multiple-channel material deposition device for dispensing a liquid adhesive composition and selected reinforcement materials at predetermined proportions onto a work surface; (2) during the material deposition process, moving the deposition device and the work surface relative to each other in an X-Y plane defined by first and second directions and in a Z direction orthogonal to the X-Y plane so that the materials are deposited to form a first layer of the shape; (3) repeating these steps to deposit multiple layers for forming a three-dimensional preform shape; and (4) periodically hardening the adhesive to rigidize individual layers of the preform. These steps are preferably executed under the control of a computer system by taking additional steps of (5) creating a geometry of the shape on the computer with the geometry including a plurality of segments defining the preform shape and each segment being preferably coded with a reinforcement composition defining a specific proportion of different reinforcement materials; (6) generating programmed signals corresponding to each of the segments in a predetermined sequence; and (7) moving the deposition device and the work surface relative to each other in response to these programmed signals. Preferably, the system is also operated to generate a support structure for any un-supported feature of the 3-D preform shape

Global exponential convergence of delayed inertial Cohen–Grossberg neural networks

In this paper, the exponential convergence of delayed inertial Cohen–Grossberg neural networks (CGNNs) is studied. Two methods are adopted to discuss the inertial CGNNs, one is expressed as two first-order differential equations by selecting a variable substitution, and the other does not change the order of the system based on the nonreduced-order method. By establishing appropriate Lyapunov function and using inequality techniques, sufficient conditions are obtained to ensure that the discussed model converges exponentially to a ball with the prespecified convergence rate. Finally, two simulation examples are proposed to illustrate the validity of the theorem results

Genetic Engineering of Starch Biosynthesis in Maize Seeds for Efficient Enzymatic Digestion of Starch during Bioethanol Production

Maize accumulates large amounts of starch in seeds which have been used as food for human and animals. Maize starch is an importantly industrial raw material for bioethanol production. One critical step in bioethanol production is degrading starch to oligosaccharides and glucose by alpha-amylase and glucoamylase. This step usually requires high temperature and additional equipment, leading to an increased production cost. Currently, there remains a lack of specially designed maize cultivars with optimized starch (amylose and amylopectin) compositions for bioethanol production. We discussed the features of starch granules suitable for efficient enzymatic digestion. Thus far, great advances have been made in molecular characterization of the key proteins involved in starch metabolism in maize seeds. The review explores how these proteins affect starch metabolism pathway, especially in controlling the composition, size and features of starch. We highlight the roles of key enzymes in controlling amylose/amylopectin ratio and granules architecture. Based on current technological process of bioethanol production using maize starch, we propose that several key enzymes can be modified in abundance or activities via genetic engineering to synthesize easily degraded starch granules in maize seeds. The review provides a clue for developing special maize cultivars as raw material in the bioethanol industry

Modeling Multi-wavelength Pulse Profiles of Millisecond Pulsar PSR B1821-24

PSR B1821$-$24 is a solitary millisecond pulsar (MSP) which radiates multi-wavelength pulsed photons. It has complex radio, X-ray and $\gamma$-ray pulse profiles with distinct peak phase-separations that challenge the traditional caustic emission models. Using the single-pole annular gap model with suitable magnetic inclination angle ($\alpha=40^\circ$) and viewing angle ($\zeta=75^\circ$), we managed to reproduce its pulse profiles of three wavebands. It is found that the middle radio peak is originated from the core gap region at high altitudes, and the other two radio peaks are originated from the annular gap region at relatively low altitudes. Two peaks of both X-ray and $\gamma$-ray wavebands are fundamentally originated from annular gap region, while the $\gamma$-ray emission generated from the core gap region contributes somewhat to the first $\gamma$-ray peak. Precisely reproducing the multi-wavelength pulse profiles of PSR B1821$-$24 enables us to understand emission regions of distinct wavebands and justify pulsar emission models.Comment: Accepted for publication in Ap

Global attractive set of neural networks with neutral item

This paper investigates the global attractive set of neural networks with neutral item. To better deal with the neutral terms, different types of activation functions are considered. Based on matrix measures, inequality techniques, and Lyapunov theory, three new types of Lyapunov functions are designed to find the global attractive set of the system. We give out a simulation example to verify the validity of theory results. The result is very inclusive, whether the system has equilibrium or not. As long as the system is stable, we can find its global attractive set

Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering

Collaborative filtering (CF) is a widely employed technique that predicts user preferences based on past interactions. Negative sampling plays a vital role in training CF-based models with implicit feedback. In this paper, we propose a novel perspective based on the sampling area to revisit existing sampling methods. We point out that current sampling methods mainly focus on Point-wise or Line-wise sampling, lacking flexibility and leaving a significant portion of the hard sampling area un-explored. To address this limitation, we propose Dimension Independent Mixup for Hard Negative Sampling (DINS), which is the first Area-wise sampling method for training CF-based models. DINS comprises three modules: Hard Boundary Definition, Dimension Independent Mixup, and Multi-hop Pooling. Experiments with real-world datasets on both matrix factorization and graph-based models demonstrate that DINS outperforms other negative sampling methods, establishing its effectiveness and superiority. Our work contributes a new perspective, introduces Area-wise sampling, and presents DINS as a novel approach that achieves state-of-the-art performance for negative sampling. Our implementations are available in PyTorch

Fluid mineralization of the Dongtongyu gold deposit in the southern margin of North China craton: Evidence from microthermometry and composition of fluid inclusions

In this study, petrographic, microthermometric, and synchrotron radiation X-ray fluorescence (SRXRF) analyses of fluid inclusions were conducted to shed light on the mineralization mechanism of the Dongtongyu deposit and provide some evidence of the relationship among CO2, Au, and other ore elements (e.g., Cu, Fe, Zn, and Pb) in ore-forming fluids. The ore-forming fluid is characterized as the H2O–CO2–NaCl system with medium–high temperatures and low salinities. Four structural mineralization stages are distinguished: Pyrite-quartz (Stage 1), gold-quartz-pyrite (Stage 2), gold-quartz-polymetallic sulfide (Stage 3), and quartz-calcite (Stage 4). Fluid inclusions in Stages 1–3 are dominated by the H2O–CO2 type, and most of them contain liquid H2O and liquid CO2 at room temperature. The melting temperatures (Tm-CO2 = −82.1°C to −57.5°C) of solid CO2 in Stage 1 are relatively low. The values of Tm-CO2 in Stages 2–3 are quite close, with ranges of −60.5°C to −56.5°C and −59.2°C to −58.6°C, respectively. The melting temperatures of clathrate in Stages 1–3 are −2.7°C to +7.8°C, −5.5°C to +7.8°C, and +3.7°C to +7.2°C. The homogenization temperatures of the CO2 phase in the H2O–CO2 inclusions of the three stages are measured as −7.5°C to +31.7°C, −7.5°C to +29.3°C, and 7.1°C to +24.1°C. The total homogenization temperatures in Stages 1–3 are 180°C–394°C, 202°C–305°C, and 224°C–271°C, with salinities of 4.3 wt.%–18.2 wt% NaCl, 4.3 wt.%–20.0 wt% NaCl, and 5.3 wt.%–11.0 wt% NaCl, respectively. The laser Raman spectroscopy results show that the CO2–H2O inclusions in the quartz veins contain abundant CO2 and CH4. The SRXFR results show that most of the elements, especially As, Te, and Cu, are more enriched in liquid CO2 than in liquid H2O. The elements of Au, Fe, Ni, Cu, and Pb have higher concentrations in H2O–CO2-type fluid inclusions in Stage 2 than other fluid inclusions in Stages 1–2, suggesting that gold mineralization is closely related to CO2-rich fluids. During the fluid evolution process, fluid immiscibility is an important mineralization mechanism of gold. The increase in CO2 and CH4 and the decrease in the fluid temperature might promote fluid immiscibility

Complicated asymptotic behavior exponents for solutions of the evolution p-Laplacian equation with absorption

Abstract In this paper, we investigate how the initial value belonging to spaces W σ ( R N ) $W_{\sigma}(\mathbb{R}^{N})$ ( 0 < σ < N $0<\sigma<N$ ) affects the complicated asymptotic behavior of solutions for the Cauchy problem of the evolution p-Laplacian equation with absorption. In fact, we reveal the fact that σ = p q − p + 1 $\sigma=\frac{p}{q-p+1}$ is the critical exponent for the complicated asymptotic behavior of the solutions