正确表面预处理对涂料干膜杀菌剂抗微生物活性的影响

通过使用墙体杀菌清洁与非杀菌清洁后涂料干膜的性能比较，评价了杀菌清洗对提高涂料干膜性能的有效性，揭示了怎样用杀菌清洁提高杀菌系统的特性。同时，比较了传统杀菌剂和新式杀菌剂的性能差别。     

Oxidation of Butane to Maleic Anhydride using Vanadium Phosphate Catalysts: Comparison of Operation in Aerobic and Anaerobic Conditions using a Gas-gas Periodic Flow Reactor

The use of a periodic flow reactor is described for the oxidation of butane to maleic anhydride to compare the catalytic performance of vanadium phosphate catalysts operating under aerobic and anaerobic conditions. It is found that for the catalyst prepared via a standard VPO method, operation in the absence of oxygen leads to a very small enhancement in selectivity when butane concentrations in the range 0.9–2.9% are used. Operation in the absence of oxygen leads to very small differences in conversion such that the overall yield is enhanced and this effect is maximised for reactor feeds containing 1.5% butane. However, the enhancement is negligible when the catalyst is operated at high conversion required for commercial operation, indicating that reactors operating with continuous flow with aerobic conditions are preferred. Similar experiments are conducted for a catalyst prepared by the VPD method and, in contrast, this catalyst gives lower butane conversion and maleic anhydride selectivity when operated in the absence of oxygen.     

Two-dimensional correlation relaxometry studies of cement pastes performed using a new one-sided NMR magnet

We present preliminary results of the first NMR T₁-T₂ two-dimensional relaxation correlation experiments performed using a one-sided NMR system in cement based materials. Two-dimensional correlation relaxometry has itself only recently been demonstrated in cement paste where it proved to be a particularly sensitive probe of pore-water dynamics providing direct information on exchange of water between the gel and capillary pore networks. Further to this we have observed differences in the structural development of a selection of cement pastes throughout the early stages of hydration and verified the theoretical frequency dependence of the ratio T₁ / T₂. When coupled with instrumentation developments in one-sided NMR magnets the way is opened to detailed, spatially resolved studies of the development of hydration and porosity in the surface layers (top 50 mm) of cementitious materials. A new magnet, suitable for such applications, is discussed.     

Terpolymers. II. Mechanical properties and transition temperatures of terpolymers of vinyl stearate,vinyl acetate,and vinyl chloride

Vinyl stearate was studied as a major internal plasticizer in terpolymers containing vinyl acetate and vinyl chloride. The terpolymers were prepared by systematically replacing vinyl acetate by close increments of vinyl stearate starting with combinations of vinyl acetate and vinyl chloride, in increments, over all compositions. For comparison of properties, a complete range of copolymers of vinyl stearate and vinyl chloride, as well as mixtures of poly(vinyl chloride) and di-2-ethylhexyl phthalate (DOP) were also made. The external plasticizer was more efficient in reducing the glass temperature than was vinyl stearate. The decline in T_g with weight fraction of plasticizer was linear for the copolymers and terpolymers but concave downward with the liquid diluent. The linear decline was shown to involve mere additivity of the free volume contributed by each side-chain methylene (or methyl) group in both vinyl esters to reducing T_g. The mechanism of the diluent system was more complex. However, the magnitude of the reduction of tensile modulus at a given weight fraction of DOP could be equaled or exceeded by the same amount of vinyl stearate, by increasing the vinyl acetate content of the base copolymer to 40 mole-% or more. Unfortunately, the ultimate strengths and elongations of internally plasticized systems were reduced more than those of the mixtures at comparable compositions. Vinyl stearate was found to markedly retard photolytic degradation compared to both vinyl acetate and the external plasticizer in unstabilized samples having nearly the same thermal treatment. The effect was greater than could be ascribed to dilution by the long alkyl group. The production of a stearoyl radical more stable than the radicals initiating dehydrochlorination is suggested as a possible mechanism.     

The role of the automation development group in analytical research and development at Dupont Merck

Laboratory robotics has been firmly established in many non-QC laboratories as a valuable tool for automating pharmaceutical dosage form analysis. Often a single project or product line is used to justify an initial robot purchase thus introducing robotics to the laboratory for the first time. However, to gain widespread acceptance within the laboratory and to justify further investment in robotics, existing robots must be used to develop analyses for existing manual methods as well as new projects beyond the scope off the original purchase justification. The Automation Development Group in Analytical Research and Development is a team of analysts primarily devoted to developing new methods and adapting existing methods for the robot. This team approach developed the expertise and synergy necessary to significantly expand the contribution of robotics to automation in the authors'' laboratory.     

Absorption of silicone fluid in a silicone elastomer

Measurements have been made of the absorption properties of a silicone fluid in a silicone elastomer, Aircast 3700, at temperatures between 0 and 150 °C. It was found that the diffusivity could be described by Arrhenius' law. The saturation fluid content was 20% at 0 °C, decreasing to 17% at 120 °C. The swelling was large, up to 26% at saturation, and approximately equalled the volume of fluid absorbed. A reverse thermal effect was observed and an attempt has been made to explain it.     

Isolation kernel: the X factor in efficient and effective large scale online kernel learning

Large scale online kernel learning aims to build an efficient and scalable kernel-based predictive model incrementally from a sequence of potentially infinite data points. Current state-of-the-art large scale online kernel learning focuses on improving efficiency. Two key approaches to gain efficiency through approximation are (1) limiting the number of support vectors, and (2) using an approximate feature map. They often employ a kernel with a feature map with intractable dimensionality. While these approaches can deal with large scale datasets efficiently, this outcome is achieved by compromising predictive accuracy because of the approximation. We offer an alternative approach that puts the kernel used at the heart of the approach. It focuses on creating a sparse and finite-dimensional feature map of a kernel called Isolation Kernel. Using this new approach, to achieve the above aim of large scale online kernel learning becomes extremely simple—simply use Isolation Kernel instead of a kernel having a feature map with intractable dimensionality. We show that, using Isolation Kernel, large scale online kernel learning can be achieved efficiently without sacrificing accuracy.

     

Conspiracy vs science: A large-scale analysis of online discussion cascades

World Wide Web - With the emergence and rapid proliferation of social media platforms and social networking sites, recent years have witnessed a surge of misinformation spreading in our daily life....     

Designing biomass supply chains within planetary boundaries

The design of sustainable supply chains, which recently emerged as an active area of research in process systems engineering, is vital to ensure sustainable development. Despite past and ongoing efforts, the available methods often overlook impacts beyond climate change or incorporate them via standard life cycle assessment metrics that are hard to interpret from an absolute sustainability viewpoint. We here address the design of biomass supply chains considering critical ecological limits of the Earth—planetary boundaries—which should never be surpassed by anthropogenic activities. Our method relies on a mixed-integer linear program that incorporates a planetary boundaries-based damage model to quantify absolute sustainability precisely. We apply this approach to the sugarcane-to-ethanol industry in Argentina, identifying the optimal combination of technologies and network layout that minimize the impact on these ecological boundaries. Our framework can find applications in a wide range of supply chain problems related to chemicals and fuels production, energy systems, and agriculture planning.