Temperature cycling and its effect on mechanical behaviours of highporosity chalks

Temperature history can have a significant effect on the strength of water-saturated chalk.In this study,hydrostatic stress cycles are applied to understand the mechanical response of chalk samples exposed to temperature cycling between each stress cycle,compared to the samples tested at a constant temperature.The total accumulated strain during a stress cycle and the irreversible strain are reported.Chalk samples from Kansas(USA)and Mons(Belgium),with different degrees of induration(i.e.amount of contact cementation),were used.The samples were saturated with equilibrated water(polar)and nonpolar Isopar H oil to quantify water weakening.All samples tested during 10 stress cycles with varying temperature(i.e.temperature cycled in between each stress cycle)accumulated more strain than those tested at constant temperatures.All the stress cycles were performed at 30℃.The two chalk types behaved similarly when saturated with Isopar H oil,but differently when saturated with water.When saturated with water,the stronger Kansas chalk accumulated more total strain and more irreversible strain within each stress cycle than the weaker Mons chalk.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

Occurrence and diversity of Listeria spp. in seafood processing plant environments

Listeria contamination in processing plant environments is a major issue for the seafood industry worldwide; faster and more reliable results are therefore desired for early detection and monitoring of environmental Listeria spp. This study aimed to gain a better understanding of the prevalence and diversity of Listeria spp., and to evaluate a rapid detection method, the 3M Molecular Detection Assay (MDA) Listeria, for its ability to detect Listeria spp. in environmental samples from seafood processing plants. Duplicate environmental sponge samples (n = 444) were collected from 152 different sites within three seafood processing plants, and analyzed for Listeria spp. by the MDA method (after 26 and 48 h of enrichment) and the U.S. Food and Drug Administration Bacteriological Analytical Manual method. Overall, detection of Listeria spp. by the two methods did not differ significantly (p > 0.05); 11 (4.9%) and 13 (5.9%) samples were positive for Listeria spp. by the MDA and FDA-BAM method, respectively. The sensitivity of the MDS was 87.0% (95% CI: 77.4–96.6%), specificity was 97.6% (95% CI: 95.5–99.7%), accuracy was 95.3%, and the positive predictive value was 89.4% (95% CI: 80.5–98.2%). Classification of 19 Listeria isolates by partial SigB sequencing analysis identified three allelic types. Twelve of these isolates were ATs 58 and 60 which were classified as Listeria monocytogenes lineage I and serotypes 1/2b, 3b, 4b, 4d, 4e, by multiplex-PCR serotyping. Six Listeria isolates were classified as Listeria innocua (AT31). Our data show that the 3M Molecular Detection Assay Listeria provides rapid and reliable results for detection and monitoring of Listeria spp., which are important for seafood processing plants. Effective Listeria monitoring programs will allow for improved development of Listeria control measures in order to minimize cross-contamination in finished products.     

Non-chaotic and chaotic propagation of stationary and dynamic images through MVKS turbulence

Anisoplanatic electromagnetic (EM) propagation across a turbulent atmosphere has been recently examined for an unmodulated carrier propagating over an image-bearing transparency through optical lensing, and for the embedded information inside a carrier recovered using heterodyning and digital demodulation. Carrier modulation yielded better recovery than simple lens-based imaging. A possible mitigation strategy is proposed whereby the image information is encrypted on an RF chaotic carrier, thereafter secondarily embedded onto an optical carrier. Results based on the modified von Karman (MVKS) and the Hufnagel-Valley (H-V) models showed that the signal/image recovery under turbulence is improved compared with non-chaotic propagation. The case of time-varying/dynamic images is also taken up; it is demonstrated via cross-correlation products that turbulence is mitigated by the use of chaotic carrier encryption. Overall, transmission via chaos offers mitigation against distortions due to turbulence along with the security feature inherent via the chaos keys which prevent signal recovery without key-matching.     

Sparse non-convex Lp regularization for cone-beam X-ray luminescence computed tomography

Cone-beam X-ray luminescence computed tomography (CB-XLCT) is an attractive hybrid imaging modality, and it has the potential of monitoring the metabolic processes of nanophosphors-based drugs in vivo. However, the XLCT imaging suffers from a severe ill-posed problem. In this work, a sparse nonconvex L_p (0?p?L₁ regularization. Further, an iteratively reweighted split augmented lagrangian shrinkage algorithm (IRW_SALSA-L_p) was proposed to efficiently solve the non-convex L_p (0?p?p-values (1/16, 1/8, 1/4, 3/8, 1/2, 5/8, 3/4, 7/8) in both 3D digital mouse experiments and in vivo experiments. The results demonstrate that the proposed non-convex methods outperform L₂ and L₁ regularization in accurately recovering sparse targets in CB-XLCT. And among all the non-convex p-values, our L_p(1/4?p?相似文献   

Animations showing Lego manipulative tasks: Three potential moderators of effectiveness

Evidence suggests that transient visual information, such as animations, may be more challenging to learn than static visualizations. However, when a procedural-manipulative task is involved, our evolved embodied cognition seems to reverse this transitory challenge. Hence, for object manipulative tasks, instructional animations may be more suitable than statics. We investigated this argument further by comparing animations with statics using a Lego task shown to university students, by examining three potential moderators of effectiveness: (a) the environment of manipulation (virtual or physical), (b) the quality of visual information (focused or unfocused), and (c) the presence of hands (no hands or with hands). In Experiment 1 we found an advantage of animation over statics, and no differences among the environments. In Experiment 2, we again observed an animation advantage, a small advantage of focused static information compared to unfocused static information, and a positive effect of not showing the hands.     

Reducing numerical dissipation in smoke simulation

Numerical dissipation acts as artificial viscosity to make smoke viscous. Reducing numerical dissipation is able to recover visual details smeared out by the numerical dissipation. Great efforts have been devoted to suppress the numerical dissipation in smoke simulation in the past few years. In this paper we investigate methods of combating the numerical dissipation. We describe visual consequences of the numerical dissipation and explore sources that introduce the numerical dissipation into course of smoke simulation. Methods are investigated from various aspects including grid variation, high-order advection, sub-grid compensation, invariant conservation, and particle-based improvement, followed by discussion and comparison in terms of visual quality, computational overhead, ease of implementation, adaptivity, and scalability, which leads to their different applicability to various application scenarios.     

Learning fuzzy controllers in mobile robotics with embedded preprocessing

The automatic design of controllers for mobile robots usually requires two stages. In the first stage, sensorial data are preprocessed or transformed into high level and meaningful values of variables which are usually defined from expert knowledge. In the second stage, a machine learning technique is applied to obtain a controller that maps these high level variables to the control commands that are actually sent to the robot. This paper describes an algorithm that is able to embed the preprocessing stage into the learning stage in order to get controllers directly starting from sensorial raw data with no expert knowledge involved. Due to the high dimensionality of the sensorial data, this approach uses Quantified Fuzzy Rules (QFRs), that are able to transform low-level input variables into high-level input variables, reducing the dimensionality through summarization. The proposed learning algorithm, called Iterative Quantified Fuzzy Rule Learning (IQFRL), is based on genetic programming. IQFRL is able to learn rules with different structures, and can manage linguistic variables with multiple granularities. The algorithm has been tested with the implementation of the wall-following behavior both in several realistic simulated environments with different complexity and on a Pioneer 3-AT robot in two real environments. Results have been compared with several well-known learning algorithms combined with different data preprocessing techniques, showing that IQFRL exhibits a better and statistically significant performance. Moreover, three real world applications for which IQFRL plays a central role are also presented: path and object tracking with static and moving obstacles avoidance.     

A first-principles investigation on mechanical and metallic properties of titanium carbides under pressure

The titanium carbides are potential candidates to achieve both high hardness and refractory property. We carried out a structural search for titanium carbides at three pressures of 0 GPa, 30 GPa and 50 GPa. A phase diagram of the Ti-C system at 0 K was obtained by elucidating formation enthalpies as a function of compositions, and their mechanical and metallic properties of titanium carbides were investigated systematically. We also discussed the relation of titanium concentration to the both mechanical and metallic properties of titanium carbides. It has been found that the average valence electron density and tractility improved at higher concentrations of titanium, while the degree of covalent bonding directionality decreased. To this effect, the hardness of titanium carbide decreases as the content of titanium increases. Our results indicated that the titanium content significantly affected the metallic properties of the Ti-C system.     

现场总线在冶炼烟气制酸系统中的应用实践

分析了冶炼烟气制酸工艺的特点，介绍了由PROFIBUS-DP现场总线构建的冶炼厂烟气制酸监控系统，详细介绍了其硬件配置及相应的软件设计。