Natural sunlight ageing of control and sterilized poly(ethylene terephthalate): Two‐dimensional infrared correlation spectroscopic investigation

Attenuated total reflection Fourier transform infrared (ATR‐FTIR) and two‐dimensional correlation (2D‐COS) spectroscopies were utilized to probe the structural changes occurring upon sunlight ageing up to 6 months in air atmosphere of both control and sterilized poly(ethylene terephthalate), (PET) bottles.Two dominant reactions were found; namely oxidation of the carbonyl groups and trans to gauche transformation of the ethylene glycole units. Oxidation manifested itself by the progressive development of a distinct band at 1690 cm^?1assigned to the antisymmetric stretching of the carbonyl band in an aromatic carboxylic acid. Sterilizing the bottles by E‐beam or Gamma rays prior to ageing reduced the correlation intensity of the band at 1690 cm^?1, and led to the presence of higher molecular weight compounds such as terephthalic acid in stored water. The infrared spectroscopy combined with 2D‐COS provides a powerful tool to investigate chemical and stero‐chemical modification of polymers. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134 , 44736.     

A bivariate negative binomial model to explain traffic accident migration

The phenomenon of "regression to the mean" is now widely known in the study of the effectiveness of remedial treatment of traffic accident blackspots. What happens is that the criterion used for selection of sites at which treatment is to be applied gives rise to bias in the estimate of the effectiveness: the conditional expectation of the after frequency is less than the true mean, even if the treatment is totally ineffective. It has been reported in some previous studies that accident "migration" has been observed. This is the phenomenon whereby the accident rate apparently rises at sites that are untreated but that are neighbours to treated sites. If this were a genuine effect, it would have serious implications for the assessment of remedial treatments. This paper aims to explain this migration effect in purely probabilistic terms, without recourse to the concept of physical migration. The model used is a new bivariate negative binomial distribution, incorporating spatial correlation between the true mean site accident rates. As with the regression to mean effect, the migration effect can then be explained in terms of the conditioning implicit in the selection process.     

High resistivity BaTiO3 ceramics sintered in CO-CO2 atmospheres

A barium titanate ceramic containing 13.5 mol % calcium zirconate was doped with up to 3 mol % of oxides of various metals that were considered likely on the basis of ionic size and valence to enter the small cation lattice with charge less than 4+. It was hoped in this way to compensate electrically for loss of oxygen during sintering in CO-CO₂ mixtures, so as to obtain high resistivity dielectrics and allow the use of base metal electrodes in a monolithic capacitor. Doping with approximately 0.5 mol % Mn, Co, or Mg produced the highest resistivities, and dielectrics with nickel electrodes and relative permittivity up to 10 000 were obtained with resistivity in excess of 10¹² cm at room temperature. When the doped ceramic sintered in contact with nickel, the grain structure and permittivity-temperature characteristics depended on the oxygen partial pressure of the sintering atmosphere, apparently influenced by dissolution of Ni into the ceramic.     

A new DCT audio watermarking scheme based on preliminary MP3 study

In this paper, a new audio watermarking scheme operating in the frequency domain and based on neural network architecture is described. The watermark is hidden into the middle frequency band after performing a Discrete Cosine transform (DCT). Embedding and extraction of the watermark are based on the use of a back-propagation neural network (BPNN) architecture. In addition, the selection of frequencies and the block hiding the watermark are based on a preliminary study of the effect of MP3 compression at several rates on the signal. Experimental results show that the proposed technique presents good robustness and perceptual quality results. We also investigate the application of the proposed technique in video watermarking. Traditional techniques have used audio channel as supplementary embedding space and adopt state-of-the art techniques that resist to MP3 compression attack. In these techniques, the MPEG compression attack is only evaluated on the video part and the audio part is kept unaffected. In this paper, we adapt the preliminary MP3 study to video watermarking technique but with a preliminary study of the MPEG compression applied to the audio channel. Here again, we notice that the application of the preliminary MPEG study to the audio channel improves the robustness of the video watermarking scheme though keeping high-quality watermarked video sequences.     

Modularity-based decompositions for valued CSP

This paper addresses combinatorial problems that can be expressed as Valued Constraint Satisfaction Problems (VCSPs). In the VCSP framework, the constraints are defined by valuation functions to reflect several constraint violation levels. Despite the NP-hardness of VCSPs, tractable versions can be obtained by forcing the allowable valuation functions to have specific mathematical properties. This is the case of VCSPs with submodular valuation functions only. In this paper, we propose a problem decomposition scheme for binary VCSPs that takes advantage of modular valuation functions even when the studied problem is not limited to these functions. Modular functions are less frequent than submodular ones but, in compensation, they are easier to process. The proposed scheme works within a backtrack-based search and consists in decomposing the original problem into a set of modular, and then tractable, subproblems. Our decomposition scheme is distinguished by the possibility of instantiating variables by assigning to them subsets of values instead of single values.     

Robust weighted kernel logistic regression in imbalanced and rare events data

Recent developments in computing and technology, along with the availability of large amounts of raw data, have contributed to the creation of many effective techniques and algorithms in the fields of pattern recognition and machine learning. The main objectives for developing these algorithms include identifying patterns within the available data or making predictions, or both. Great success has been achieved with many classification techniques in real-life applications. With regard to binary data classification in particular, analysis of data containing rare events or disproportionate class distributions poses a great challenge to industry and to the machine learning community. This study examines rare events (REs) with binary dependent variables containing many more non-events (zeros) than events (ones). These variables are difficult to predict and to explain as has been evidenced in the literature. This research combines rare events corrections to Logistic Regression (LR) with truncated Newton methods and applies these techniques to Kernel Logistic Regression (KLR). The resulting model, Rare Event Weighted Kernel Logistic Regression (RE-WKLR), is a combination of weighting, regularization, approximate numerical methods, kernelization, bias correction, and efficient implementation, all of which are critical to enabling RE-WKLR to be an effective and powerful method for predicting rare events. Comparing RE-WKLR to SVM and TR-KLR, using non-linearly separable, small and large binary rare event datasets, we find that RE-WKLR is as fast as TR-KLR and much faster than SVM. In addition, according to the statistical significance test, RE-WKLR is more accurate than both SVM and TR-KLR.     

Investigation of the effect of machining parameters on the surface quality of machined brass (60/40) in CNC end milling—ANFIS modeling

Brass and brass alloys are widely employed industrial materials because of their excellent characteristics such as high corrosion resistance, non-magnetism, and good machinability. Surface quality plays a very important role in the performance of milled products, as good surface quality can significantly improve fatigue strength, corrosion resistance, or creep life. Surface roughness (Ra) is one of the most important factors for evaluating surface quality during the finishing process. The quality of surface affects the functional characteristics of the workpiece, including fatigue, corrosion, fracture resistance, and surface friction. Furthermore, surface roughness is among the most critical constraints in cutting parameter selection in manufacturing process planning. In this paper, the adaptive neuro-fuzzy inference system (ANFIS) was used to predict the surface roughness in computer numerical control (CNC) end milling. Spindle speed, feed rate, and depth of cut were the predictor variables. Experimental validation runs were conducted to validate the ANFIS model. The predicted surface roughness was compared with measured data, and the maximum prediction error for surface roughness was 6.25 %, while the average prediction error was 2.75 %.     

Association of 210Po(210Pb), 239+240Pu and 241Am with different mineral fractions of a beach sand at Seascale, Cumbria, UK

Automotive catalytic converters, in which Pt, Pd and Rh (platinum-group elements; PGEs) are the active components for eliminating several noxious components from exhaust fumes, have become the main source of environmental urban pollution by PGEs. This work reports on the catalyst morphology through changes in catalyst surface by scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDX) and laser-induced breakdown spectrometry (LIBS) from fresh to aged catalytic converters. The distribution of these elements in the fresh catalysts analysed (Pt-Pd-Rh gasoline catalyst) is not uniform and occurs mainly in a longitudinal direction. This heterogeneity seems to be greater for Pt and Pd. PGEs released by the catalysts, fresh and aged 30,000 km, were studied in parallel. Whole raw exhaust fumes from four catalysts of three different types were also examined. Two of these were gasoline catalysts (Pt-Pd Rh and Pd-Rh) and the other two were diesel catalysts (Pt). Samples were collected following the 91,441 EUDC driving cycle for light-duty vehicle testing. The results show that at 0 km the samples collected first have the highest content of particulate PGEs and although the general tendency is for the release to decrease with increasing number of samples taken, exceptions are frequent. At 30,000 km the released PGEs in gasoline and diesel catalysts decreased significantly. For fresh gasoline catalysts the mean of the total amount released was approximately 100, 250 and 50 ng km(-1) for Pt, Pd and Rh, respectively. In diesel catalysts the Pt release varied in the range 400-800 ng km-1. After ageing the catalysts up to 30,000 km, the gasoline catalysts released amounts of Pt between 6 and 8 ng km(-1), Pd between 12 and 16 ng km(-1) and Rh between 3 and 12 ng km(-1). In diesel catalysts the Pt release varied in the range 108-150 ng km(-1). The soluble portion of PGEs in the HNO3 collector solution represented less than 5% of the total amount for fresh catalysts. For 30,000 km the total amount of soluble PGEs released was similar or slightly higher than for 0 km.     

Arsenic in coastal waters of South Australia

Surface seawater samples from South Australian coastal locations were analysed for dissolved inorganic arsenic [As(III) + As(V)], arsenite [As(III)] and particulate arsenic.Dissolved inorganic arsenic concentrations ranged from 1.10 to 1.61 μg As l^?1 (average 1.3 ± 0.1 μg As l^?1) with 1.2–4.3% (average 2.7%) present as arsenite. Particulate arsenic concentrations were below the limit of detection (0.0006 μg As l^?1) at most sampling stations.     

Denitrification in a natural wetland receiving secondary treated effluent

The potential of a natural wetland as a site for nitrogen removal from secondary treated effluent was examined by investigating the distribution of denitrification rates and activity in soils and decaying plant material. Field measurements of soil Eh, pH and temperature showed that the effluent inflow favours denitrification by lowering Eh, maintaining pH 6.4–6.7, and raising soil temperature. Analysis of soil concentrations of nitrate plus nitrite and ammonium ions shows that the effluent inflow increased the concentrations of inorganic nitrogen in the soil, and encouraged higher rates of denitrification. Denitrification rates measured by an acetylene blockage technique were highest in soil samples from downstream of the effluent inflow, with the maximum rates being recorded in soils from 0 to 60 cm and in decaying plant material lying on the soil surface. Both nitrate plus nitrite concentration and denitrification activity declined rapidly below 6 cm in upstream and downstream soil samples. Denitrification rates in the natural wetland are increased by the addition of secondary treated effluent, and make a year-round contribution to the removal of nitrogen from the wastewater. Rates of nitrogen removal in the wetland could be increased by encouraging greater spatial and temporal interaction of the effluent amended water with the sites of highest denitrification activity.