Experimental and theoretical study of skylight polarization transmitted through Snell's window of a flat water surface

The celestial polarization pattern may be scrambled by refraction at the air-water interface. This polarization pattern was examined in shallow waters with a submersible polarimeter, and it was calculated by using land measurements ('semiempirical predictions') and models of the skylight polarization. Semiempirically predicted and measured e-vector orientations were significantly similar. Conversely, predicted percent polarization was correlated but lower than measurements. Percent polarization depended on wavelength, where at high sun altitudes maximal percent polarization generally appeared in the UV and red spectral regions. The wavelength dependency of polarization may lead to differential spectral sensitivity in polarization-sensitive animals according to time and type of activity.     

Microstructure and mechanical properties of hot extruded 6016 aluminum alloy/graphite composites

The incorporation of graphite particles into AA6016 aluminum alloy matrix to fabricate metal/ceramic composites is still a great challenge and various parameters should be considered. In this study, dense AA6016 aluminum alloy/(0-20 wt%) graphite composites have successfully been fabricated by powder metallurgy process. At first, the mixed aluminum and graphite powders were cold compacted at 200 MPa and then sintered at 500 ℃ for 1 h followed by hot extrusion at 450 ℃. The influence of ceramic phases(free graphite and in-situ formed carbides) on microstructure, physical and mechanical properties of the produced composites were finally investigated. The results show that the fabricated composites have a relative density of over 98%. SEM observations indicate that the graphite has a good dispersion in the alloy matrix even at high graphite content. Hardness of all the produced composites was higher than that of aluminum alloy matrix. No cracks were observed at strain less than 23% for all hot extruded materials.Compressive strength, reduction in height, ultimate tensile stress, fracture stress, yield stress, and fracture strain of all Al/graphite composites were determined by high precision second order equations. Both compressive and ultimate tensile strengths have been correlated to microstructure constituents with focusing on the in-situ formed ceramic phases, silicon carbide(SiC) and aluminum carbide(Al_4 C_3). The ductile fracture mode of the produced composites became less dominant with increasing free graphite content and in-situ formed carbides. Wear resistance of Al/graphite composites was increased with increasing graphite content. Aluminum/20 wt% graphite composite exhibited superior wear resistance over that of AA6016 aluminum alloy.     

Ultrafast gas chromatographic separation of organophosphor and organosulfur compounds utilizing a microcountercurrent flame photometric detector

A microcountercurrent flame photometric detector (microcc-FPD) was adapted and optimized for ultrafast gas chromatographic (GC) separation and detection of organophosphor (OP) and organosulfur (OS) compounds on short chromatographic columns. Air and hydrogen are introduced to the microcc-FPD from opposite directions, creating a hydrogen-rich flame. In this microcc-FPD, combustion takes place between the burner tips without touching them. The separation between the tips and the flame reduces heat loss from the flame to the surrounding environment, resulting in low hydrogen consumption and a compact flame. The microcc-FPD is capable of detecting very narrow (13 ms) chromatographic peaks. An ultrafast GC separation of a group of six OP and OS compounds is achieved within less than 5 s using fast temperature programming of a 0.5-m-long microbore column. Very fast separations are also demonstrated on a 1-m-long microfabricated column consisting of 150-microm-wide, 240-microm-deep channels, etched in a 1.9-cm square silicon chip, covered with a Pyrex wafer, and statically coated with dimethyl polysiloxane. With a hydrogen flow rate of 10 mL/min, the detection limit for OP is 12 pg of P/s and 3 ng of S/s for OS compounds at a signal-to-noise ratio of 2. The coupling of a microfabricated column and a miniature FPD is an important step toward the development of a miniaturized GC-FPD capable of ultrafast detection of low levels of OP and OS compounds.     

Modelling the heart as a communication system

Electrical communication between cardiomyocytes can be perturbed during arrhythmia, but these perturbations are not captured by conventional electrocardiographic metrics. We developed a theoretical framework to quantify electrical communication using information theory metrics in two-dimensional cell lattice models of cardiac excitation propagation. The time series generated by each cell was coarse-grained to 1 when excited or 0 when resting. The Shannon entropy for each cell was calculated from the time series during four clinically important heart rhythms: normal heartbeat, anatomical reentry, spiral reentry and multiple reentry. We also used mutual information to perform spatial profiling of communication during these cardiac arrhythmias. We found that information sharing between cells was spatially heterogeneous. In addition, cardiac arrhythmia significantly impacted information sharing within the heart. Entropy localized the path of the drifting core of spiral reentry, which could be an optimal target of therapeutic ablation. We conclude that information theory metrics can quantitatively assess electrical communication among cardiomyocytes. The traditional concept of the heart as a functional syncytium sharing electrical information cannot predict altered entropy and information sharing during complex arrhythmia. Information theory metrics may find clinical application in the identification of rhythm-specific treatments which are currently unmet by traditional electrocardiographic techniques.     

The Hierarchical Hidden Markov Model: Analysis and Applications

We introduce, analyze and demonstrate a recursive hierarchical generalization of the widely used hidden Markov models, which we name Hierarchical Hidden Markov Models (HHMM). Our model is motivated by the complex multi-scale structure which appears in many natural sequences, particularly in language, handwriting and speech. We seek a systematic unsupervised approach to the modeling of such structures. By extending the standard Baum-Welch (forward-backward) algorithm, we derive an efficient procedure for estimating the model parameters from unlabeled data. We then use the trained model for automatic hierarchical parsing of observation sequences. We describe two applications of our model and its parameter estimation procedure. In the first application we show how to construct hierarchical models of natural English text. In these models different levels of the hierarchy correspond to structures on different length scales in the text. In the second application we demonstrate how HHMMs can be used to automatically identify repeated strokes that represent combination of letters in cursive handwriting.     

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.     

Effects of three cellulose gums on the texture profile and sensory properties of low fat frankfurters

Composition, textural, viscoelastic, hydration, colour, and sensory attributes of regular and low fat pork/beef frankfurters with and without cellulose gums (carboxymethyl cellulose (CMC) and two types of microcrystalline cellulose (MCC-I and II)) were investigated. Fat was replaced with water in the low fat products. Moisture loss during cooking was reduced in low fat products from 10 to 6% because of the addition of CMC; however, both MCC increased moisture loss by 12–15%. CMC addition also increased the amount of free water. The high fat product was lighter (higher 'L') than the reduced fat frankfurters; gums did not appreciably change the colour. The viscoelastic properties (relaxation time, elastic moduli) were unaffected by the changes in fat level. Product hardness, brittleness, gumminess and chewiness increased with the decrease in fat level. MCC-II improved the textural properties of the low fat product to those of the high fat product. Sensory panel results indicated a decrease in tenderness with low fat and this was not improved by MCC-II. Overall, acceptability scores indicated that all the products (high and low fat) were acceptable.     

Two phase biomass air-steam gasification model for fluidized bed reactors: Part II—model sensitivity

A sensitivity analysis was performed on the two phase biomass gasification model developed by Sadaka et al. (Biomass Bioenergy) to test its response to variations in three operating parameters (fluidization velocity, steam flow rate and biomass to steam ratio). The model performance criteria included bed temperature, gas compositions, higher heating value and gas production rate. The results showed that the model was sensitive to changes in all operating parameters. The temperatures of the reactor were more influenced by changes in the steam flow rate than those of fluidization velocity and biomass to steam ratio. The steam flow rate has the most effect on the mole fractions of CH₄, and CO₂ followed by the biomass to steam ratio and then the fluidization velocity. In the case of H₂, and CO the biomass to steam ratio has the most effect on their mole fractions followed by the steam flow rate and then fluidization velocity. The fluidization velocity has the most effect on the mole fraction of N₂. The biomass to steam ratio has the most effect on the gas higher heating value and the gas production rate.