Optimization of Pathogen Capture in Flowing Fluids with Magnetic Nanoparticles

Magnetic nanoparticles have been employed to capture pathogens for many biological applications; however, optimal particle sizes have been determined empirically in specific capturing protocols. Here, a theoretical model that simulates capture of bacteria is described and used to calculate bacterial collision frequencies and magnetophoretic properties for a range of particle sizes. The model predicts that particles with a diameter of 460 nm should produce optimal separation of bacteria in buffer flowing at 1 L h⁻¹. Validating the predictive power of the model, Staphylococcus aureus is separated from buffer and blood flowing through magnetic capture devices using six different sizes of magnetic particles. Experimental magnetic separation in buffer conditions confirms that particles with a diameter closest to the predicted optimal particle size provide the most effective capture. Modeling the capturing process in plasma and blood by introducing empirical constants (c_e), which integrate the interfering effects of biological components on the binding kinetics of magnetic beads to bacteria, smaller beads with 50 nm diameters are predicted that exhibit maximum magnetic separation of bacteria from blood and experimentally validated this trend. The predictive power of the model suggests its utility for the future design of magnetic separation for diagnostic and therapeutic applications.     

Effect of Ti/N Ratio on Impact Strength of High Strength Pipe Steel Welded Joint Heat-Affected Zone

Metallurgist - Kinetics of austenite grain growth within a heat-affected zone is studied for low carbon low-alloy steels of different alloying composition. The effect of Ti/N ratio on the metal...     

High‐intensity sweeteners in espresso coffee: ideal and equivalent sweetness and time–intensity analysis

The efficient substitution of sucrose by a sweetener in beverages requires the application of some sensory techniques. First, one must determine the concentrations of the sweeteners under study, equivalent in sweetness to the ideal sucrose concentration. In addition, it is fundamental to determine which is most similar to sucrose. The objectives of this study were to determine the ideal sweetness for espresso coffee and the equivalent concentrations in sweetness of different sweeteners, as well as characterise the time–intensity profile of each sweetener in relation to sweetness. The sweeteners evaluated were sucralose, aspartame, neotame, a cyclamate/saccharin mixture (2:1) and stevia. The sucrose concentration considered ideal by consumers was 12.5% (w/v), and the equivalent concentrations of the sweeteners were 0.0159% for sucralose, 0.0549% for aspartame, 0.0016% for neotame, 0.0359% for the cyclamate/saccharin mixture and 0.0998% for stevia. The time–intensity analysis indicated that possibly the sweeteners neotame, aspartame and sucralose would be the best substitutes for sucrose.     

Technical and economic analysis of solvent-based lithium-ion electrode drying with water and NMP

Processing lithium-ion battery (LIB) electrode dispersions with water as the solvent during primary drying offers many advantages over N-methylpyrrolidone (NMP). An in-depth analysis of the comparative drying costs of LIB electrodes is discussed for both NMP- and water-based dispersion processing in terms of battery pack $/kWh. Electrode coating manufacturing and capital equipment cost savings are compared for water vs. conventional NMP organic solvent processing. A major finding of this work is that the total electrode manufacturing costs, whether water- or NMP-based, contribute about 8–9% of the total pack cost. However, it was found that up to a 2?×?reduction in electrode processing (drying and solvent recovery) cost can be expected along with a $3–6?M savings in associated plant capital equipment (for a plant producing 100,000 10-kWh Plug-in Hybrid Electric Vehicle (PHEV) batteries) using water as the electrode solvent. This paper shows a different perspective in that the most important benefits of aqueous electrode processing actually revolve around capital equipment savings and environmental stewardship and not processing cost savings.     

UPR: deadlock-free dynamic network reconfiguration by exploiting channel dependency graph compatibility

The Journal of Supercomputing - Deadlock-free dynamic network reconfiguration process is usually studied from the routing algorithm restrictions and resource reservation perspective. The dynamic...     

Semantic word shifts in a scientific domain

Understanding semantic word shifts in scientific domains is essential for facilitating interdisciplinary communication. Using a data set of published papers in the field of information retrieval (IR), this paper studies the semantic shifts of words in IR based on mining per-word topic distribution over time. We propose that semantic word shifts not only occur over time, but also over topics. The shifts are examined from two perspectives, the topic-level and the context-level. According to the over-time word-topic distribution, stable words and unstable words are recognized. The diverging and converging trends in the unstable type reveal characteristics of the topic evolution process. The context-level shifts are further detected by similarities between word vectors. Our work associates semantic word shifts with the evolving of topics, which facilitates a better understanding of semantic word shifts from both topics and contexts.     

Do funded papers attract more usage?

Research funding has been seen as one of the most important resource in the reward system of science. And usage of publications denotes an interesting perspective of user behavior in scientific communication. This study aims to address the relationship between funding and Usage Count, which is a new metrics item established on the platform of Web of Science. Full records of 300,010 articles published in 2013 were downloaded in October 2015, and divided into six disciplines, including information science library science, education educational research, economics, computer science, materials science, and chemistry. Seven indicators were proposed to measure the impact, including Funding rate, Citation per paper, Usage rate, Usage per paper, Citation difference, Usage difference, and Conversion rate. It concluded funding has impact on usage and citation, and funded papers attract more usage, but varying in different disciplines. Usage Count can be used in the extension of citation metrics but with limits. This study originally engages with usage metrics and detected that there is positive correlation between usage and funding.