Fabrication of very high aspect ratio metal nanowires by a self-propulsion mechanism

A novel synthesis method of very high aspect ratio metal nanowires is described. The synthesis utilizes a nanoporous membrane as a template and self-electrophoresis as a directed force that continuously push formed nanowires out of the pores in a rate that is identical to the rate of their elongation. As a result, while the pores of membranes are only 6 microm long, the formed nanowires could be more than 100 microm long.     

Aberration-free superresolution imaging via binary speckle pattern encoding and processing

We present an approach that provides superresolution beyond the classical limit as well as image restoration in the presence of aberrations; in particular, the ability to obtain superresolution while extending the depth of field (DOF) simultaneously is tested experimentally. It is based on an approach, recently proposed, shown to increase the resolution significantly for in-focus images by speckle encoding and decoding. In our approach, an object multiplied by a fine binary speckle pattern may be located anywhere along an extended DOF region. Since the exact magnification is not known in the presence of defocus aberration, the acquired low-resolution image is electronically processed via a parallel-branch decoding scheme, where in each branch the image is multiplied by the same high-resolution synchronized time-varying binary speckle but with different magnification. Finally, a hard-decision algorithm chooses the branch that provides the highest-resolution output image, thus achieving insensitivity to aberrations as well as DOF variations. Simulation as well as experimental results are presented, exhibiting significant resolution improvement factors.     

Effect of supramolecular structure on polymer nanofibre elasticity

Polymer materials of reduced size and dimensionality, such as thin films, polymer nanofibres and nanotubes, exhibit exceptional mechanical properties compared with those of their macroscopic counterparts. We discuss here the abrupt increase in Young's modulus in polymer nanofibres. Using scaling estimation we show that this effect occurs when, in the amorphous (non-crystalline) part of the nanofibres, the transversal size of regions consisting of orientation-correlated macromolecules is comparable to the nanofibre diameter, thereby resulting in confinement of the supramolecular structure. We suggest that in polymer nanofibres the resulting supramolecular microstructure plays a more dominant role in the deformation process than previously thought, challenging the commonly held view that surface effects are most significant. The concept we develop also provides a way to interpret the observed--but not yet understood--temperature dependence of Young's modulus in nanofibres of different diameters.     

Encapsulation of bacteria and viruses in electrospun nanofibres

Bacteria and viruses were encapsulated in electrospun polymer nanofibres. The bacteria and viruses were suspended in a solution of poly(vinyl alcohol) (PVA) in water and subjected to an electrostatic field of the order of 1?kV?cm(-1). Encapsulated bacteria in this work, (Escherichia coli, Staphylococcus albus) and bacterial viruses (T7, T4, λ) managed to survive the electrospinning process while maintaining their viability at fairly high levels. Subsequently the bacteria and viruses remain viable during three months at -20 and -55?°C without a further decrease in number. The present results demonstrate the potential of the electrospinning process for the encapsulation and immobilization of living biological material.     

Imagined positive emotions and inhibitory control: The differentiated effect of pride versus happiness.

Inhibitory control is a cognitive mechanism that contributes to successful self-control (i.e., adherence to a long-term goal in the face of an interfering short-term goal). This research explored the effect of imagined positive emotional events on inhibition. The authors proposed that the influence of imagined emotions on inhibition depends on whether the considered emotion corresponds to the attainment of a long-term goal (i.e., pride) or a short-term goal (i.e., happiness). The authors predicted that in an antisaccade task that requires inhibition of a distractor, imagining a happiness-eliciting event is likely to harm inhibitory processes compared with imagining a pride-eliciting event, because the former but not the latter primes interfering short-term goals. The results showed that imagining a happiness-eliciting event decreased inhibition relative to imagining a pride-eliciting event. The results suggest a possible mechanism underlying the role of imagined positive emotions in pursuit of goals that require self-control. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effects of monoglyceride content,cooling rate and shear on the rheological properties of olive oil/monoglyceride gel networks

Functionality of conventional fat spreads can be achieved without hydrogenation by the formation of stable network structures upon cooling of mixtures of monoglycerides (MGs) and vegetable oils from the melt. Such mixtures are healthy substitutes for margarine and butter. The effects of MG content, cooling rate and shear on the temperature ramp, mechanical spectra and hardness of olive oil/MG gel networks were investigated. A minimum MG volume fraction was necessary for formation of a gelled network, but this concentration was less than that needed for a space‐filling network structure. Onset of gel network or structure formation was indicated by a sudden divergence in value of the elastic modulus G′. The temperature at onset of structure formation, T_o, final G′ value and network hardness all increased with increase in MG content. High cooling rates led to low final G′ values but harder networks, and vice versa. Maximum gel network development occurred when moderate shear (about 300 s^?1) was applied at incipient gelation. Copyright © 2004 Society of Chemical Industry     

Premembranes for porogen-derived membranes and thermal decomposition of porogens

Various t-butyl and di-t-butyl esters, N-boc and di-N-boc amines, metal salts of N-boc amino acid, and glycerol–formic acid esters are potential porogens for porogen-derived membranes. Introduction of more than 20 such compounds into polysulfone or poly(vinyl chloride) films was studied. Transparency, IR spectra, changes in glass transition temperature, and differential scanning calorimetry were used to differentiate between molecular dispersion and formation of micro phases. The results show that for many of the studied additives more than 10% by weight can be practically molecularly dispersed in the polymers. The upper limit of porogen concentration in premembranes depends on characteristics of the polymer and of the porogen, on casting solvent composition, and on drying procedure. Metal salts of N-boc amino acids were found to be suitable heat-decomposable porogens. Their decomposition in premembranes proceeds in two stages, in the first of which 2 C₄H₈ + 2CO₂ are released per salt molecule. The metal complex formed goes through decarboxylation at a higher temperature. A heating procedure for completion of the first decomposition stage and for avoiding the second was determined.     

Multiple order model migration and optimal model selection for online glucose prediction in Type 1 diabetes

To address the problem of insufficient available modeling data for glucose prediction, as well as modeling burden, a model migration method was developed in a previous work to quickly transfer an old model to a new subject using a simple parameter adjustment. However, this method, which is referred to as first‐order model migration (FOMM), only considers a single order for each exogenous input, and may not produce an optimal model structure for accurate prediction. To overcome this problem, a multiple order model migration (MOMM) algorithm is proposed in this study. For different numbers of modeling samples, including glucose and two exogenous inputs (meal and insulin), the optimal modeling method may be different, and therefore, must be properly determined for each modeling scenario. First, the optimal model order is determined for each input and a multiple order prediction model is used. Then, a MOMM algorithm is developed based on particle swarm optimization (PSO) to simultaneously revise multiple parameters. The multiple order parameters of each input in the old model are quickly customized so that the revised model can be used for new subjects with desirable prediction accuracy. In particular, the influence of the number of modeling samples is analysed to check the applicability of different methods; this analysis determines the appropriate selection guidelines for the optimal model in response to different data sizes. The proposed method was evaluated using thirty in silico subjects and clinical data from seven individuals with Type 1 diabetes mellitus (DM). Overall, the MOMM algorithm presented superior results when the time period for collecting the samples was larger than 10 h (50 samples). In particular, the size of the modeling samples was separated into three different regions by evaluating the glucose prediction performance and the comparison between different algorithms for both in silico and clinical subjects. In Region I, the FOMM method achieves the best performance. In Region II, the MOMM method should be used and the prediction accuracy is superior in Region II in general. With enough samples (Region III), the subject‐dependent model (SM) algorithm can be chosen. The MOMM algorithm is demonstrated to be able to transfer models for new subjects with improved model structure. © 2017 American Institute of Chemical Engineers AIChE J, 64: 822–834, 2018     

Online Learning versus Offline Learning

We present an off-line variant of the mistake-bound model of learning. This is an intermediate model between the on-line learning model (Littlestone, 1988, Littlestone, 1989) and the self-directed learning model (Goldman, Rivest & Schapire, 1993, Goldman & Sloan, 1994). Just like in the other two models, a learner in the off-line model has to learn an unknown concept from a sequence of elements of the instance space on which it makes guess and test trials. In all models, the aim of the learner is to make as few mistakes as possible. The difference between the models is that, while in the on-line model only the set of possible elements is known, in the off-line model the sequence of elements (i.e., the identity of the elements as well as the order in which they are to be presented) is known to the learner in advance. On the other hand, the learner is weaker than the self-directed learner, which is allowed to choose adaptively the sequence of elements presented to him.We study some of the fundamental properties of the off-line model. In particular, we compare the number of mistakes made by the off-line learner on certain concept classes to those made by the on-line and self-directed learners. We give bounds on the possible gaps between the various models and show examples that prove that our bounds are tight.Another contribution of this paper is the extension of the combinatorial tool of labeled trees to a unified approach that captures the various mistake bound measures of all the models discussed. We believe that this tool will prove to be useful for further study of models of incremental learning.     

Connectors, splices, and couplers for infrared transmitting optical fibers

Connectors, splices, and couplers are widely used in silica optical fiber systems. Until now they have not been developed for mid-infrared fibers, in spite of the recognized need for such elements in many applications such as spectroscopy, radiometry, and heterodyne detection. We describe the construction and the optical and mechanical properties of such optical components for infrared transmitting silver halide optical fibers.