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     

Thin films of ZrO2 metal organic chemical vapor deposition

ZrO₂ layers were deposited for the purpose of obtaining high dielectric constant insulating layers for capacitance applications. Trifluoroacety lacetonate of zirconium was used as the source material in our open MOCVD system. Layer thickness was in the range 300–1500 Å, the substrate being degenerate n-type silicon wafers. Under optimum conditions layers with good adhesion and uniformity were obtained. The layers were polycrystalline with characteristic linear dimensions of 400 Å. Electrical measurements were used for characterization and the relative dielectric constants obtained were 30 ± 1.     

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.     

Low temperature synthesis of pseudobinary chalcogenides

Solid solutions of nine pseudobinary metal chalcogenides: (PbSn)Te, (PbSn)Se, (HgCd)Te, (HgCd)Se, (HgZn)Te, (CdZn)Te, (PbGe)Te, Cd(TeSe) and Pb(TeSe) were prepared. Complete reaction was observed at temperatures significantly lower than the respective melting points in 3–7 days, except for the Cd(TeSe) system. Homogenization required higher temperatures, but still below the melting points, and durations of up to 14 days. The alloy compositions were determined by X-ray diffraction.     

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.     

The languages FCP(:) and FCP(:,?)

The language FCP(:,?) is the outcome of attempts to integrate the best of several flat concurrent logic programming languages, including Flat GHC, FCP (↓, |) and Flat Concurrent Prolog, in a single consistent framework. FCP(:) is a subset of FCP(:, ?), which is a variant of FPP(↓, |) and employs concepts of the concurrent constraint framework of cc(↓, |). FCP(:, ?) is a language which is strong enough to accommodate all useful concurrent logic programming techniques, including those which rely on atomic test unification and read-only variables, yet incorporates the weaker languages mentioned as subsets. This allows the programmer to remain within a simple subset of the language such as Flat GHC when the full power of atomic unification or read-only variables is not needed.     

Examining for possible non-thermal effects during heating in a microwave oven

The assumption that the thermal effect (heating) is the sole factor that should be considered when a microwave source is applied has been debated by many reports, often claiming that athermal (non-thermal) effects exist as well. Such effects are claimed to change the chemical, biochemical, or the physical behaviour of some systems while the temperature and all other parameters remain unaltered. The possibility of an athermal effect was tested in a number of chemical, biological and physical systems in a very well controlled, high radiation intensity system (2.45 GHz, up to 1000 W/kg, with continuous radiation up to 48 h). The systems that were tested included: Maillard reaction, protein denaturation and polymer solubility, mutagenesis of bacteria, mutarotation equilibrium of α/β-d-glucose, and saturation solubility of NaCl. All data failed to show any significant athermal effects. The results of this study are in contrast to what has been previously reported for some of the tested systems.