Unusual Two-Step Assembly of a Minimalistic Dipeptide-Based Functional Hypergelator

Self-assembled peptide hydrogels represent the realization of peptide nanotechnology into biomedical products. There is a continuous quest to identify the simplest building blocks and optimize their critical gelation concentration (CGC). Herein, a minimalistic, de novo dipeptide, Fmoc-Lys(Fmoc)-Asp, as an hydrogelator with the lowest CGC ever reported, almost fourfold lower as compared to that of a large hexadecapeptide previously described, is reported. The dipeptide self-assembles through an unusual and unprecedented two-step process as elucidated by solid-state NMR and molecular dynamics simulation. The hydrogel is cytocompatible and supports 2D/3D cell growth. Conductive composite gels composed of Fmoc-Lys(Fmoc)-Asp and a conductive polymer exhibit excellent DNA binding. Fmoc-Lys(Fmoc)-Asp exhibits the lowest CGC and highest mechanical properties when compared to a library of dipeptide analogues, thus validating the uniqueness of the molecular design which confers useful properties for various potential applications.     

Wavefront reduction using graphs,neural networks and genetic algorithm

This paper presents an algorithm for nodal numbering in order to obtain a small wavefront. Element clique graphs are employed as the mathematical models of finite element meshes. A priority function containing five vectors is used, which can be viewed as a generalization of Sloan's function. These vectors represent different connectivity properties of the graph models. Unlike Sloan's algorithm, which uses two fixed coefficients, here, five coefficients are employed, based on an evaluation by artificial neural networks. The networks weights are obtained using a simple genetic algorithm. Examples are included to illustrate the performance of the present hybrid method. Copyright © 2004 John Wiley & Sons, Ltd.     

Maximizing learning without sacrificing the fun: Stealth assessment,adaptivity and learning supports in educational games

In this study, we investigated the validity of a stealth assessment of physics understanding in an educational game, as well as the effectiveness of different game-level delivery methods and various in-game supports on learning. Using a game called Physics Playground, we randomly assigned 263 ninth- to eleventh-grade students into four groups: adaptive, linear, free choice and no-treatment control. Each condition had access to the same in-game learning supports during gameplay. Results showed that: (a) the stealth assessment estimates of physics understanding were valid—significantly correlating with the external physics test scores; (b) there was no significant effect of game-level delivery method on students' learning; and (c) physics animations were the most effective (among eight supports tested) in predicting both learning outcome and in-game performance (e.g. number of game levels solved). We included student enjoyment, gender and ethnicity in our analyses as moderators to further investigate the research questions.     

Design,Facile Synthesis and Characterization of Porphyrin-Zirconium-Ferrite@SiO2 Core-Shell and Catalytic Application in Cyclohexane Oxidation

Silicon - In this study, a new magnetic ZrFe2O4@SiO2-TCPP nanocatalyst with high efficiency was used for the oxidation of cyclohexane to cyclohexanone (Ke) and cyclohexanol (Al). The mesoporous...     

Experimental determination of gas holdup and volumetric mass transfer coefficient in a jet bubbling reactor

The hydrodynamics and mass transfer characteristics of a lab-scale jet bubbling reactor(JBR) including the gas holdup, volumetric mass transfer coefficient and specific interfacial area were assessed experimentally investigating the influence of temperature, p H and superficial gas velocity. The reactor diameter and height were 11 and 30 cm,respectively. It was equipped with a single sparger, operating at atmospheric pressure, 20 and 40℃, and two p H values of 3 and 6. The height of the liquid was 23 cm, while the superficial gas velocity changed within 0.010–0.040 m·s~(-1) range. Experiments were conducted with pure oxygen as the gas phase and saturated lime solution as the liquid phase. The liquid-side volumetric mass transfer coefficient was determined under unsteady-state oxygen absorption in a saturated lime solution. The gas holdup was calculated based on the liquid height change, while the specific interfacial area was obtained by a physical method based on the bubble size distribution(BSD) in different superficial gas velocities. The results indicated that at the same temperature but different p H, the gas holdup variation was negligible, while the liquid-side volumetric mass transfer coefficient at the p H value of 6 was higher than that at the p H = 3. At a constant p H but different temperatures, the gas holdup and the liquid-side volumetric mass transfer coefficients at 40℃ were higher than that of the same at 20℃. A reasonable and appropriate estimation of the liquid-side volumetric mass transfer coefficient(kla) in a pilot-scale JBR was provided which can be applied to the design and scale-up of JBRs.     

Photo Sequencing

A group of people taking pictures of a dynamic event with their mobile phones is a popular sight. The set of still images obtained this way is rich in dynamic content but lacks accurate temporal information. We propose a method for photo-sequencing—temporally ordering a set of still images taken asynchronously by a set of uncalibrated cameras. Photo-sequencing is an essential tool in analyzing (or visualizing) a dynamic scene captured by still images. The first step of the method detects sets of corresponding static and dynamic feature points across images. The static features are used to determine the epipolar geometry between pairs of images, and each dynamic feature votes for the temporal order of the images in which it appears. The partial orders provided by the dynamic features are not necessarily consistent, and we use rank aggregation to combine them into a globally consistent temporal order of images. We demonstrate successful photo-sequencing on several challenging collections of images taken using a number of mobile phones.     

Synthesis and characterization of hydrophilic nanocomposite coating on glass substrate

Hydrophilic coatings based on 3‐glicidoxy propyl trimethoxy silane (GPTMS) and polyethylene glycol (PEG) were prepared with the incorporation of tetramethoxysilane (TMOS) and silica nanoparticle colloidal suspension by a sol–gel process. Characterization of the coatings has been performed by Fourier Transform Infrared (FTIR) and Attenuated Total Reflectance Infrared (ATR‐IR) techniques. Morphological properties were characterized by Scanning Electron Microscopy (SEM). The distribution of Si atoms in the hybrid system was obtained by Si mapping. The particle size in sol solution of the coating was measured by light scattering analyzer. Optical properties were characterized by using UV–vis spectrophotometer. The hydrophilicity of the coating was determined by contact angle measurements, and also the results have been confirmed by surface energy and water uptake investigations. The obtained results indicate that the surfactants affected the contact angles remarkably but did not change the transparency. It has been found that applying silica nano particles leads to coatings with different properties than those using TMOS, while siloxane contents were the same in these two set of coatings. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 5322–5329, 2006     

铸铁坩锅抗铝融蚀等离子喷涂技术

针对提高化铝用铸铁坩埚抗融蚀寿命的实际问题,选用价格较低、耐高温、抗融蚀性好的Ａｌ２Ｏ３陶瓷材料作为坩埚内壁的工作层,采用等离子喷涂技术来提高其抗融蚀性。但由于Ａｌ２Ｏ３陶瓷涂层的致密性差、结合强度及抗热震寿命低等缺点,不适宜化铝坩埚在７２０℃长时间加温,且液铝呈搅拌行为的工作条件下使用。本文在Ａｌ２Ｏ３喷涂粉末中加入１３％ＴｉＯ２,促使涂层的组织结构发生变化,提高了涂层的结合强度,改善了涂层的致     

A probabilistic alternative to regression suites

Automated regression suites are essential in developing large applications, while maintaining reasonable quality and timetables. The main argument against the automation of regression suites, in addition to the cost of creation and maintenance, is the observation that if you run the same test many times, it becomes increasingly less likely to find bugs. To alleviate such problems, a new regression suite practice, using random test generators to create regression suites on-the-fly, is becoming more common. In this practice, instead of maintaining tests, we generate test suites on-the-fly by choosing several specifications and generating a number of tests from each specification.     

Automatic boosting of cross-product coverage using Bayesian networks

Closing the feedback loop from coverage data to the stimuli generator is one of the main challenges in the verification process. Typically, verification engineers with deep domain knowledge manually prepare a set of stimuli generation directives for that purpose. Bayesian networks based CDG (coverage directed generation) systems have been successfully used to assist the process by automatically closing this feedback loop. However, constructing these CDG systems requires manual effort and a certain amount of domain knowledge from a machine learning specialist. We propose a new method that boosts coverage in the early stages of the verification process with minimal effort, namely a fully automatic construction of a CDG system that requires no domain knowledge. Experimental results on a real-life cross-product coverage model demonstrate the efficiency of the proposed method.