Applying several machine learning approaches for prediction of unconfined compressive strength of stabilized pond ashes

This paper evaluates the potential of five modeling approaches, namely M5 model tree, random forest, artificial neural networks, support vector machines and Gaussian processes, for the prediction of unconfined compressive strength of stabilized pond ashes with lime and lime sludge. The study not only presents five models for the same set of data but also compares the overall performance of them. Dataset used consists of 255 samples acquired from laboratory experiments. Out of the total, 170 randomly chosen samples were used for training and remaining 85 were used for testing the models. Input dataset consists of eight parameters (uniformity coefficient, coefficient of curvature, maximum dry density, optimum moisture content, lime, lime sludge, curing period and 7-day soaked California bearing ratio), while the output is UCS value at 7, 28, 45, 90 and 180 days of curing. Comparisons of results propose that Gaussian processes modeling strategy works well and the overall performance was substantially nearer to the exact agreement line. As a result of GP model, higher value of CC = 0.997 and lower values of RMSE = 23.016 kPa and MAE = 16.455 were obtained for testing the dataset. Sensitivity analysis suggests that lime, lime sludge, curing period and California bearing ratio are the significant parameters for predicting the unconfined compressive strength of stabilized pond ashes. The results confirmed that GP models are in a position to predict the unconfined compressive strength of stabilized pond ashes with an excessive degree of accuracy; however, GP modeling approach proves that this approach is more economical and less difficult in comparison with tedious laboratory work.

     

Slow Light Transmission in Chalcogenide Photonic Crystal Waveguide

The slow light propagation in a line defect waveguide in chalcogenide photonic crystal of As2S3 rods in air medium has been investigated.It is found that the filling factor of the chalcogenide photonic crystal and the size of defect rods decide the propagation of the guided mode.An increase in the filling factor results in a sharp decrease of the group velocity in the photonic crystal waveguide.It has been demonstrated that,by tuning the filling factor and size of defect rods,the group velocity will be redu...     

Silicon Based One-Dimensional Photonic Crystal as a TM-Mode Filter

The effect of temperature and angle of incidence on the transmission spectra of a one dimensional photonic crystal for TE and TM polarizations has been studied. For a range of angle of incidence from 0° to 60°, the proposed structure works as an omni-directional reflector. For other angles of incidence more than 60°, the structure works as a selective TM-polarization filter i.e. a filter which completely blocks TE-polarized waves but allows certain frequencies of TM-polarized waves. At an angle of incidence of 89°, the structure works as a multi channel optical filter without introducing any defect in the geometry. Also, this multi-channel filter can work as a tunable filter by varying the temperature of the structure and the number of layers in the geometry. Only for two bi-layers the proposed structure works as a single channel filter. Therefore, such types of structure are easier to fabricate and may be cost effective as compared to defect one-dimensional photonic crystals.     

Room-temperature kinetics of castor-oil-based polyurethane/poly(2-hydroxyethyl methacrylate) interpenetrating polymer networks

The kinetics aspects of the formation of castor-oil-based polyurethane/poly(2-hydroxyethyl methacrylate) interpenetrating polymer networks (IPNs) were studied. The effect of parameters such as the polyurethane content, the activator, and acrylic cross-linker on the kinetics of formation of IPN networks was examined at room temperature. The formation of the individual networks, polyurethane, poly(2-hydroxethyl methacrylate), and their IPNs, was studied by measuring the decrease of absorbance of characteristic absorption peak of each system using IR spectroscopy. © 1994 John Wiley & Sons, Inc.     

Body temperature around induced estrus in dairy cows

The overall objective of this study was to study the influence of induced estrus on body temperature, comparing 5 distinct intervals around induced estrus and to determine the diurnal pattern from 4 ± 1 d before to 4 ± 1 d after induced estrus. Sixteen estrous cycles of 9 postpartum dairy cows were synchronized with 2 injections of PGF_2α, 10 d apart. After the second PGF_2α injection on d 10, temperature loggers were inserted into the vaginal cavity for a 12 ± 1-d period. Two days later, a third dose of PGF_2α was injected to induce estrus. After confirmation of a corpus luteum, loggers were removed on d 5 ± 1. Observation of estrus, rectal palpation, and ultrasound scanning to determine ovulation were carried out every 4 ± 1 h, beginning at 12 h after the third PGF_2α injection. Blood samples from the vena coccygea mediana were collected twice daily from d 11 to 12 and every 4 ± 1 h after the third PGF_2α injection until ovulation. Vaginal temperature was recorded every 5 min and averaged to hourly means for the following 5 periods: 1) 48 h preceding the third PGF_2α injection, 2) from the third PGF_2α injection to first signs of estrus, 3) estrus to ovulation, 4) a 4-h interval in which ovulation occurred, and 5) a 96-h post-ovulation period. High body temperatures (39.0 ± 0.5°C) and low progesterone (P4) concentrations (<0.5 ng/mL) were observed during estrus, whereas low body temperatures were observed from PGF_2α injection to estrus (38.6 ± 0.3°C) and around ovulation (38.5 ± 0.2°C), respectively. An association between body temperature and serum P4 concentrations did not exist. However, P4 concentrations on d 11 and 12 were high (5.0 ± 1.5 ng/mL) and decreased (0.9 ± 0.2 ng/mL) after ovulation. Diurnal temperature rhythms were similar before and after estrus. Vaginal temperature before estrus (d 11 and 12) was slightly (0.1°C) higher compared with the post-ovulation period.     

Bearing ratio and leachate analysis of pond ash stabilized with lime and lime sludge

Recycling of industrial waste is one of the effective ways to overcome their disposal problem. Ash produced by thermal power plants and lime sludge produced by paper mills require huge disposal land and may create environmental problems such as dusting and leaching of harmful heavy metals. Stabilization of the ash can improve its engineering properties and address the environmental problems. This paper reports the laboratory test results of a Class F pond ash stabilized with lime (2%, 4%, 6% and 8% by weight) alone and in combination with lime sludge (5%, 10% and 15% by weight). The X-ray diffraction (XRD) and scanning electron micrograph (SEM) tests were also performed to identify the possible formation of crystalline phases after stabilization. The effects of lime sludge on the unsoaked and soaked bearing ratios of pond ash with different lime contents, after 7 d, 28 d and 45 d of curing, were observed. Test results indicated that the bearing ratio increased considerably up to a 4% lime content which can be taken as the optimum lime content. Further increase in lime content increased bearing ratio gradually but at a slower rate. The effect of lime sludge was more pronounced at the optimum lime content, particularly at a low curing period. Lime sludge improved the bearing ratio in soaked condition significantly. Leachate analysis of stabilized ash was performed using toxicity characteristic leaching procedure (TCLP-1311) method. The concentrations of toxic elements Zn, Cu, Cd, Ni and Cr in the stabilized mixes were lower than those in the unstabilized waste. The results indicated that the pond ash-lime-lime sludge mixes have potential application as road subbase material.     

Endogenous and exogenous progesterone influence body temperature in dairy cows

Three experiments were conducted to determine the effect of endogenous progesterone (P4) on body temperature comparing lactating, pregnant with lactating, nonpregnant cows, and to study the effect of exogenous P4 administered via a controlled internal drug release (CIDR) insert on body temperature in lactating dairy cows. Body temperature was measured vaginally and rectally using temperature loggers and a digital thermometer, respectively. In experiment 1, 10 cyclic lactating cows (3 primiparous, 7 multiparous) and 10 lactating, pregnant cows (3 primiparous, 7 multiparous) were included. Vaginal temperatures and serum P4 concentrations were greater in pregnant cows (vaginal: 0.3±0.01°C; P4: 5.5±0.4 ng/mL) compared with nonpregnant cows. In experiment 2, estrous cycles of 14 postpartum healthy, cyclic, lactating cows (10 primiparous, 4 multiparous) were synchronized, and cows were assigned randomly to 1 of 2 treatments (CIDR-P4 or CIDR-blank). A temperature logger was inserted 1 d after ovulation using a P4-free CIDR (CIDR-blank) and a CIDR containing 1.38g of P4 (CIDR-P4) in the control (n=7) and the P4-treated group (n=7), respectively. On d 3 after P4 treatment, vaginal temperature was 0.3±0.03°C greater compared with that on d 1 and d 5. In experiment 3, 9 cyclic multiparous lactating cows were enrolled 1±1 d after confirmed ovulation and a temperature logger inserted. Two days later, a CIDR-P4 was inserted on top of the CIDR-blank. On d 5±1 and d 7±1, respectively, the CIDR-P4 and CIDR-blank with the temperature logger were removed. During the CIDR-P4 treatment (48h), vaginal temperature was 0.2±0.05°C and 0.1±0.05°C greater than during the pre- and post-treatment periods (48h), respectively. Serum P4 concentration peaked during CIDR-P4 treatment (2.2±0.8 ng/mL) and was greater than during the pre-treatment period (0.2±0.2 ng/mL) for 48h. An increase in vaginal temperature could be due to endogenous and exogenous P4. However, a correlation between serum P4 concentrations and body temperature did not exist. Further investigations are warranted to better understand the pathways of the thermogenic effect of P4 on body temperature.     

Interpenetrating polymer networks from castor oil based polyurethane and poly(methyl methacrylate), III

Liquid prepolyurethanes (PPU) were obtained from castor oil and toluene-2,4-diisocyanate under different experimental conditions varying NCO/OH ratio. All these prepolyurethanes were subsequently interpenetrating with poly(methyl methacrylate) made by radical polymerization initiated with benzoyl peroxide. The novel PPU/PMMA interpenetrating polymer networks were obtained as though films by transfer moulding. They were characterized by thermal studies (DSC and TGA) and mechanical properties viz., tensile strength, modulus of elasticity, and percent elongation at break. The morphological behaviour was analyzed by scanning electron microscopy.     

A 3-D liver segmentation method with parallel computing for selective internal radiation therapy

This study describes a new 3-D liver segmentation method in support of the selective internal radiation treatment as a treatment for liver tumors. This 3-D segmentation is based on coupling a modified k-means segmentation method with a special localized contouring algorithm. In the segmentation process, five separate regions are identified on the computerized tomography image frames. The merit of the proposed method lays in its potential to provide fast and accurate liver segmentation and 3-D rendering as well as in delineating tumor region(s), all with minimal user interaction. Leveraging of multicore platforms is shown to speed up the processing of medical images considerably, making this method more suitable in clinical settings. Experiments were performed to assess the effect of parallelization using up to 442 slices. Empirical results, using a single workstation, show a reduction in processing time from 4.5 h to almost 1 h for a 78% gain. Most important is the accuracy achieved in estimating the volumes of the liver and tumor region(s), yielding an average error of less than 2% in volume estimation over volumes generated on the basis of the current manually guided segmentation processes. Results were assessed using the analysis of variance statistical analysis.