Chain extension and branching of poly(ethylene terephthalate) (PET) with di- and multifunctional epoxy or isocyanate additives: An experimental and modelling study

The effect of two difunctional chain extenders, 1,6-diisocyanatohexane (NCO) and 1,4-butanediol diglycidyl ether (EPOX), in the reactive melt-processing of a post-consumer poly(ethylene terephthalate) (r-PET) was investigated. The torque evolution during processing in a batch mixer and the molecular weight of the chain-extended r-PET, as determined by SEC analysis, were comparatively evaluated. A simple mathematical model proposed here was used to fit the obtained molecular weights. Two polyfunctional chain extenders, poly(phenyl isocyanate-co-formaldehyde) (P-NCO) and a styrene-acrylate copolymer bearing epoxide groups (P-EPOX), were also used and their reactivity was compared with that of the difunctional ones by analysing torque and melt flow rate data. The different reactivity of the two functional groups and the structure of the final polymer (either linear or branched depending on the type of chain extender) affect both crystallization behaviour and tensile properties of the modified r-PET. Fine tuning of the latter properties by suitable chain extender(s) selection and formulation is anticipated.     

Combustion irreversibilities: Numerical simulation and analysis

An exergy analysis was performed considering the combustion of methane and agro-industrial residues produced in Portugal (forest residues and vines pruning). Regarding that the irreversibilities of a thermodynamic process are path dependent, the combustion process was considering as resulting from different hypothetical paths each one characterized by four main sub-processes: reactant mixing, fuel oxidation, internal thermal energy exchange (heat transfer), and product mixing. The exergetic efficiency was computed using a zero dimensional model developed by using a Visual Basic home code. It was concluded that the exergy losses were mainly due to the internal thermal energy exchange sub-process. The exergy losses from this sub-process are higher when the reactants are preheated up to the ignition temperature without previous fuel oxidation. On the other hand, the global exergy destruction can be minored increasing the pressure, the reactants temperature and the oxygen content on the oxidant stream. This methodology allows the identification of the phenomena and processes that have larger exergy losses, the understanding of why these losses occur and how the exergy changes with the parameters associated to each system which is crucial to implement the syngas combustion from biomass products as a competitive technology.     

Particle size and magnetic properties dependence on growth temperature for rapid mixed co-precipitated magnetite nanoparticles

Magnetite nanoparticles have been prepared by co-precipitation using a custom-designed jet mixer to achieve rapid mixing (RM) of reactants in a timescale of milliseconds. The quick and stable nucleation obtained allows control of the particle size and size distribution via a more defined growth process. Nanoparticles of different sizes were prepared by controlling the processing temperature in the first few seconds post-mixing. The average size of the nanoparticles investigated using a Tecnai transmission electron microscope is found to increase with the temperature from 3.8 nm at 1 ± 1?°C to 10.9 nm for particles grown at 95 ± 1?°C. The temperature dependence of the size distribution follows the same trend and is explained in terms of Ostwald ripening of the magnetite nanoparticles during the co-precipitation of Fe(2+) and Fe(3+). The magnetic properties were studied by monitoring the blocking temperature via both DC and AC techniques. Strikingly, the obtained RM particles maintain the high magnetization (as high as ～88 A m(2) kg(-1) at 500 kA m(-1)) while the coercivity is as low as ～12 A m(-1) with the expected temperature dependence. Besides, by adding a drop of tetramethylammonium hydroxide, aqueous ferrofluids with long term stability are obtained, suggesting their suitability for applications in ferrofluid technology and biomedicine.     

Aqueous atmospheric chemistry: formation of 2,4-dinitrophenol upon nitration of 2-nitrophenol and 4-nitrophenol in solution

Field studies have shown that the powerful phytotoxic agent 2,4-dinitrophenol is very likely to form in the atmospheric aqueous phase upon nitration of 2-nitrophenol or 4-nitrophenol. However, until now, the nitration pathway and the relative importance of the two mononitrophenols as sources of 2,4-dinitrophenol were not known. The present study shows that 2,4-dinitrophenol formation from mononitrophenols can take place upon photolysis and photooxidation of nitrite/nitrous acid (NO2-/HONO) and that nitrogen dioxide plays a key role in the process. A possible pathway might be the reaction between light-excited mononitrophenols (both 2- and 4-isomers) and nitrogen dioxide, in the presence of oxygen. As an alternative, nitration might involve *NO3 + *NO2. Possible sources of nitrogen dioxide in the atmospheric aqueous phase are dissolution from the gas phase and oxidation of NO2-. In the latter case, however, it is necessary that NO2- oxidation is faster than the oxidation of mononitrophenols. This would happen, for instance, in the presence of hematite under irradiation. Radiation absorption and scattering by hematite would also inhibit the direct photolysis of nitrophenols. The formation rate and the yield of 2,4-dinitrophenol are slightly higher when starting from 2-nitrophenol than those from 4-nitrophenol, but they are compensated by the higher concentration of 4-nitrophenol in the atmospheric aqueous phase.     

Robust control through piecewise Lyapunov functions for discrete time-varying uncertain systems

This paper is concerned with the robust stabilization by state feedback of a linear discrete-time system with time-varying uncertain parameters. An optimization problem involving a set of linear matrix inequalities and scaling parameters provides both the robust feedback gain and the piecewise Lyapunov function used to ensure the closed-loop stability. In the case of linear time-varying systems involving the convex combination of two matrices, only two scaling parameters constrained into the interval [0,?1] are needed, allowing a simple numerical solution as illustrated by means of examples.     

Delay Dependent Local Stabilization Conditions for Time-delay Nonlinear Discrete-time Systems Using Takagi-Sugeno Models

International Journal of Control, Automation and Systems - We propose convex conditions for stabilization of nonlinear discrete-time systems with time-varying delay in states through a fuzzy...     

Combining time series prediction models using genetic algorithm to autoscaling Web applications hosted in the cloud infrastructure

In a cloud computing environment, companies have the ability to allocate resources according to demand. However, there is a delay that may take minutes between the request for a new resource and it being ready for using. This causes the reactive techniques, which request a new resource only when the system reaches a certain load threshold, to be not suitable for the resource allocation process. To address this problem, it is necessary to predict requests that arrive at the system in the next period of time to allocate the necessary resources, before the system becomes overloaded. There are several time series forecasting models to calculate the workload predictions based on history of monitoring data. However, it is difficult to know which is the best time series forecasting model to be used in each case. The work becomes even more complicated when the user does not have much historical data to be analyzed. Most related work considers only single methods to evaluate the results of the forecast. Other works propose an approach that selects suitable forecasting methods for a given context. But in this case, it is necessary to have a significant amount of data to train the classifier. Moreover, the best solution may not be a specific model, but rather a combination of models. In this paper we propose an adaptive prediction method using genetic algorithms to combine time series forecasting models. Our method does not require a previous phase of training, because it constantly adapts the extent to which the data are coming. To evaluate our proposal, we use three logs extracted from real Web servers. The results show that our proposal often brings the best result and is generic enough to adapt to various types of time series.     

Alkoxide-based precursors for direct drawing of metal oxide micro- and nanofibres

The invention of electrospinning has solved the problem of producing micro- and nanoscaled metal oxide fibres in bulk quantities. However, until now no methods have been available for preparing a single nanofibre of a metal oxide. In this work, the direct drawing method was successfully applied to produce metal oxide (SnO₂, TiO₂, ZrO₂, HfO₂ and CeO₂) fibres with a high aspect ratio (up to 10 000) and a diameter as small as 200 nm. The sol–gel processing includes consumption of precursors obtained from alkoxides by aqueous or non-aqueous polymerization. Shear thinning of the precursors enables pulling a material into a fibre. This rheological behaviour can be explained by sliding of particles owing to external forces. Transmission (propagation) of light along microscaled fibres and their excellent surface morphology suggest that metal oxide nanofibres can be directly drawn from sol precursors for use in integrated photonic systems.     

Dipyridamole stress echocardiography in diagnosis and prognosis of hemodialysis patients with asymptomatic coronary disease

The prevalence of coronary artery disease (CAD) is high in hemodialysis (HD) patients. The aim of the study was to assess the diagnostic and prognostic value of dipyridamole stress echocardiography (DSE) in nondiabetic HD patients without signs or symptoms of CAD. In 51 out of 158 evaluated HD patients (21 females, age 67 [33–85] years, HD duration 38 [9–271] months), resting echocardiography and DSE were performed. Exclusion criteria were known CAD, diabetes mellitus, and pulmonary and oncologic pathologies. Logistic regression analysis was carried out to identify predictors of abnormal DSE response, while Cox regression analysis was performed to determine variables associated with total and cardiovascular mortality, after 43.3 (11–60) months of follow‐up. Seven patients (14%) showed a positive response to DSE (DSE+). In 5/7, CAD was documented by angiography: All of them underwent coronary revascularization. DSE+ patients had significantly smaller body mass index than patients with a negative response (DSE‐): 21.7 ± 1.9 vs. 25.1 ± 3.4 kg/m² (p = 0.018). During follow‐up, 16 (31%) patients died. Older age hazard ratio [HR = 1.07; confidence interval (CI) = 1.01–1.12; p = 0.02] and higher plasma phosphate levels (HR = 10.41; CI = 2.30–47.17; p < 0.01) were predictors of total mortality. Male gender (HR = 22.7; CI = 1.45–354.4; p = 0.03), older age (HR = 1.24; CI = 1.03–1.50; p = 0.02), longer HD duration (HR = 1.13; CI = 1.01–1.26; p = 0.04), and positive response to DSE (HR = 5.82; CI = 1.04–32.65; p = 0.04) were associated with cardiovascular mortality. Ten percent of asymptomatic HD patients had significant CAD, but timely diagnosis did not seem to improve their prognosis. Total survival was associated with age and higher levels of plasma phosphate, while male gender, older age, longer HD duration, and DSE+ were predictors of cardiovascular mortality.