Thermal degradation of copolymers based on 2-substituted oxazolines and β-methylhydrogenitaconate

Summary The thermal stabilities of poly(-methylhydrogenitaconate-co-2-methyl-2-oxazoline) and poly(-methylhydrogenitaconate-co-2-ethyl-2-oxazoline) obtained by spontaneous copolymerization have been studied by programmed thermogravimetric analysis over the temperature range from 293 K to 773 K under a flow of nitrogen. Most of the copolymers do not show weight loss until 473 K and they degrade in one step. The kinetic parameters Ea, n and A were obtained following one method of thermogravimetric analysis. The reaction order for all copolymers was 1.0. The poly(-methylhydrogenitaconate-co-2-methyl-2-oxazoline)s were the most thermostable copolymers.     

Prediction of the percentages of cows'', goats'' and ewes'' milk in “Iberico” cheese by electrophoretic analysis of whey proteins

Stepwise multiple linear regression (SMLR) and principal components regression (PCR) have been used to predict the percentages of cows', goats' and ewes' milk in Iberico cheese, using the results obtained by electrophoretic analysis (PAGE and IEF) of whey proteins, using standard cheeses. Similar predictions of the percentages of milks from the three species were obtained when either SMLR or PCR were applied to the electrophoretic data, i.e. the optical intensity of the electrophoretic bands (PAGE or IEF) of the whey proteins. The root mean square error of prediction in cross-validation (RMSEPCV) was lower than 4% in all cases.     

Reaching the Fundamental Limitation in CO2 Reduction to CO with Single Atom Catalysts

The electrochemical CO₂ reduction reaction (CO₂RR) to value-added chemicals with renewable electricity is a promising method to decarbonize parts of the chemical industry. Recently, single metal atoms in nitrogen-doped carbon (MNC) have emerged as potential electrocatalysts for CO₂RR to CO with high activity and faradaic efficiency, although the reaction limitation for CO₂RR to CO is unclear. To understand the comparison of intrinsic activity of different MNCs, two catalysts are synthesized through a decoupled two-step synthesis approach of high temperature pyrolysis and low temperature metalation (Fe or Ni). The highly meso-porous structure results in the highest reported electrochemical active site utilization based on in situ nitrite stripping; up to 59±6% for NiNC. Ex situ X-ray absorption spectroscopy (XAS) confirms the penta-coordinated nature of the active sites. The catalysts are amongst the most active in the literature for CO₂ reduction to CO. The density functional theory calculations (DFT) show that their binding to the reaction intermediates approximates to that of Au surfaces. However, it is found that the turnover frequencies (TOFs) of the most active catalysts for CO evolution converge, suggesting a fundamental ceiling to the catalytic rates.     

Fuzzy Adaptive Control Law for Trajectory Tracking Based on a Fuzzy Adaptive Neural PID Controller of a Multi-rotor Unmanned Aerial Vehicle

International Journal of Control, Automation and Systems - This article presents a fuzzy adaptive control law (FACL) designed for tracking the trajectory of a low-scale unmanned aerial vehicle...     

Analysis of the influence of binder properties on the mechanical response of bituminous mixtures

Asphalt mixtures are composed by a mass of aggregates (more than 90% of their total weight), which are bonded by a bituminous binder. Despite the fact that the binder is not the main component of these materials (around 5% of their total weight), it exerts a high influence on their mechanical response. In this sense, the service life of asphalt pavements will directly depend on the type of binder used, and thus an adequate choice is crucial to construct more durable roads. Because of this fact, it is necessary to know the characteristics of the bitumen in order to reduce the impact of different distresses that appear on roads. For this purpose, this paper studies the influence of the binder properties in the appearance of the main distresses that affect asphalt pavements around the world (stripping, fatigue cracking and plastic deformations). Five bitumens with different properties have been analysed during this research using diverse binder (UCL, multiple stress creep and recovery test and dynamic shear rheometer time sweep) and mixture (water sensitivity, wheel tracking and UGR-FACT) tests. The results obtained show that the properties of the binder influence the long-term performance of bituminous mixtures. In this sense, it can be said that flexible binders which are able to recover plastic deformations could extend the service life of the pavements.     

Flow modeling of linear and nonlinear fluids in two scale fibrous fabrics

The fundamental macroscopic material property needed to quantify the flow in a fibrous medium viewed as a porous medium is the permeability. Composite processing models require the permeability as input data to predict flow patterns and pressure fields. As permeability reflects both the magnitude and anisotropy of the fluid/fiber resistance, efficient numerical techniques are needed to solve linear and nonlinear homogenization problems online during the flow simulation. In a previous work the expressions of macroscopic permeability were derived in a double-scale porosity medium for both Newtonian and rheo-thinning resins. In the linear case only a microscopic calculation on a representative volume is required, implying as many microscopic calculations as representative microscopic volumes exist in the whole fibrous structure. In the non-linear case, and even when the porous microstructure can be described by a unique representative volume, microscopic calculation must be carried out many times because the microscale resin viscosity depends on the macroscopic velocity, which in turn depends on the permeability that results from a microscopic calculation. Thus, a nonlinear multi-scale problem results. In this paper an original and efficient offline-online procedure is proposed for the efficient solution of nonlinear flow problems in porous media.     

Mechanical and thermal behaviour of an acrylic bone cement modified with a triblock copolymer

The basic formulation of an acrylic bone cement has been modified by the addition of a block copolymer, Nanostrength^® (NS), in order to augment the mechanical properties and particularly the fracture toughness of the bone cement. Two grades of NS at different levels of loading, between 1 and 10 wt.%, have been used. Mechanical tests were conducted to study the behaviour of the modified cements; specific tests measured the bend, compression and fracture toughness properties. The failure mode of the fracture test specimens was analysed using scanning electron microscopy (SEM). The effect of NS addition on the thermal properties was also determined, and the polymerisation reaction using differential scanning calorimetry. It was observed that the addition of NS produced an improvement in the fracture toughness and ductility of the cement, which could have a positive contribution by reducing the premature fracture of the cement mantle. The residual monomer content was reduced when the NS was added. However this also produced an increase in the maximum temperature and the heat delivered during the polymerisation of the cement.     

GraftFast Surface Engineering to Improve MOF Nanoparticles Furtiveness

Controlling the outer surface of nanometric metal–organic frameworks (nanoMOFs) and further understanding the in vivo effect of the coated material are crucial for the convenient biomedical applications of MOFs. However, in most studies, the surface modification protocol is often associated with significant toxicity and/or lack of selectivity. As an alternative, how the highly selective and general grafting GraftFast method leads, through a green and simple process, to the successful attachment of multifunctional biopolymers (polyethylene glycol (PEG) and hyaluronic acid) on the external surface of nanoMOFs is reported. In particular, effectively PEGylated iron trimesate MIL‐100(Fe) nanoparticles (NPs) exhibit suitable grafting stability and superior chemical and colloidal stability in different biofluids, while conserving full porosity and allowing the adsorption of bioactive molecules (cosmetic and antitumor agents). Furthermore, the nature of the MOF–PEG interaction is deeply investigated using high‐resolution soft X‐ray spectroscopy. Finally, a cell penetration study using the radio‐labeled antitumor agent gemcitabine monophosphate (³H‐GMP)‐loaded MIL‐100(Fe)@PEG NPs shows reduced macrophage phagocytosis, confirming a significant in vitro PEG furtiveness.     

Support environment for active rule design

The lack of tools for rule generation, analysis, and run-time monitoring appears one of the main obstacles to the widespreading of active database applications. This paper describes a complete tool environment for assisting the design of active rules applications; the tools were developed at Politecnico di Milano in the context of the IDEA Project, a 4-years Esprit project sponsored by the European Commission which was launched in June 1992. We describe tools for active rule generation, analysis, debugging, and browsing; rules are defined in Chimera, a conceptual design model and language for the specification of active rules applications. We also introduce a tool for mapping from Chimera into Oracle, a relational product supporting triggers.Most of the tools described in this paper are fully implemented and currently in operation (beta-testing) within the companies participating to the IDEA Project, with the exception of two of them (called Argonaut-V and Pandora), which will be completed by the end of 1996.Research presented in this paper is supported by Esprit project P6333 IDEA, and by ENEL contract VDS 1/94: Integrity Constraint Management     

On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets

When performing a classification task, we may find some data-sets with a different class distribution among their patterns. This problem is known as classification with imbalanced data-sets and it appears in many real application areas. For this reason, it has recently become a relevant topic in the area of Machine Learning.The aim of this work is to improve the behaviour of fuzzy rule based classification systems (FRBCSs) in the framework of imbalanced data-sets by means of a tuning step. Specifically, we adapt the 2-tuples based genetic tuning approach to classification problems showing the good synergy between this method and some FRBCSs.Our empirical results show that the 2-tuples based genetic tuning increases the performance of FRBCSs in all types of imbalanced data. Furthermore, when the initial Rule Base, built by a fuzzy rule learning methodology, obtains a good behaviour in terms of accuracy, we achieve a higher improvement in performance for the whole model when applying the genetic 2-tuples post-processing step. This enhancement is also obtained in the case of cooperation with a preprocessing stage, proving the necessity of rebalancing the training set before the learning phase when dealing with imbalanced data.