Direct characterisation of phenolic antioxidants in infusions from four Mapuche medicinal plants by liquid chromatography with diode array detection (HPLC-DAD) and electrospray ionisation tandem mass spectrometry (HPLC-ESI-MS)

A simple, fast and direct method was developed for the qualitative analysis of phenolic constituents from infusions of Mapuche medicinal plants. Teas made of Linum chamissonis Schiede, Quinchamalium chilensis Mol., Adesmia emarginata Clos. and Escallonia illinita K. Presl. were analysed by high-performance liquid chromatography with diode array detector (HPLC-DAD) and electrospray mass spectrometry (ESI-MS). This technique allowed for the first time the tentative identification of 16 phenolic compounds in E. illinita, 27 in Q. chilensis, 10 in L. chamissonis and 19 in A. emarginata. The compounds were mainly phenolic acids, flavonoid glycosides, anthocyanins and tannins. The total phenolic and flavonoid content of the infusions was assessed as well as the free radical scavenging capacity measured by the bleaching of a solution of the 2,2-diphenyl-1-picrylhydrazyl (DPPH⁻) radical. From the four species, Q. chilensis exhibited the strongest antioxidant activity with highest total phenolic and flavonoid content.     

Interaction of β‐casein with (−)‐epigallocatechin‐3‐gallate assayed by fluorescence quenching: effect of thermal processing temperature

The interactions between the flavan‐3‐ol (?)‐epigallocatechin‐3‐gallate (EGCG) and bovine β‐casein in phosphate‐buffered saline (PBS) of pH 6.5 subjected to thermal processing at various temperatures (25–100 °C) were investigated using fluorescence quenching. The results indicated that different temperatures had different effects on the structural changes and EGCG‐binding ability of β‐casein. At temperatures below 60 °C, the β‐casein–EGCG interaction changed little (P > 0.05) with increasing temperature. At temperatures above 80 °C, native assemblies of β‐casein in solution dissociated into individual β‐casein molecules and unfolded, as demonstrated by a red shift of the maximum fluorescence emission wavelength (λ_max) of up to 8.8 nm. The highest quenching constant (K_q) and the number of binding sites (n) were 0.92 (±0.01) × 10¹³ m ^?1 s^?1 and 0.73 (±0.02) (100 °C), respectively. These results provide insight into the potential of interactions between β‐casein–EGCG that may modulate bioactivity or bioavailability to be altered during thermal process.     

Investigation on PEM water electrolysis cell design and components for a HyCon solar hydrogen generator

Hydrogen as a secondary energy carrier promises a large potential as a long term storage for fluctuating renewable energies. In this sense a highly efficient solar hydrogen generation is of great interest especially in southern countries having high solar irradiation. The patented Hydrogen Concentrator (HyCon) concept yields high efficiencies combining multi-junction solar cells with proton exchange (PEM) membrane water electrolysis. In this work, a special PEM electrolysis cell for the HyCon concept was developed and investigated. It is shown that the purpose-made PEM cell shows a high performance using a titanium hybrid fiber sinter function both as a porous transport layer and flow field. The electrolysis cell shows a high performance with 1.83 V at 1 A/cm² and 24 °C working under natural convection with a commercially available catalyst coated membrane. A theoretical examination predicts a total efficiency for the HyCon module from sunlight to hydrogen of approximately 19.5% according to the higher heating value.     

Detecting component changes at run time with behavior models

Modern software systems are composed of several services which may be developed and maintained by third parties and thus they can change independently and without notice during the system’s runtime execution. In such systems, changes may possibly be a threat to system functional correctness, and thus to its reliability. Hence, it is important to detect them as soon as they happen to enable proper reaction. Change detection can be done by monitoring system execution and comparing the observed execution traces against models of the services composing the application. Unfortunately, formal specifications for services are not usually provided and developers have to infer them. In this paper we propose a methodology which exactly addresses these issues by using software behavior models to monitor component execution and detect changes. In particular, we describe a technique to infer behavior model specifications with a dynamic black box approach, keep them up-to-date with run time observations and detect behavior changes. Finally, we present a case study to validate the effectiveness of the approach in component change detection for a component that implements a complex, real communication protocol.     

Complex and dynamic population structures: synthesis, open questions, and future directions

The population structure of an evolutionary algorithm influences the dissemination and mixing of advantageous alleles, and therefore affects search performance. Much recent attention has focused on the analysis of complex population structures, characterized by heterogeneous connectivity distributions, non-trivial clustering properties, and degree–degree correlations. Here, we synthesize the results of these recent studies, discuss their limitations, and highlight several open questions regarding (1) unsolved theoretical issues and (2) the practical utility of complex population structures for evolutionary search. In addition, we will discuss an alternative complex population structure that is known to significantly influence dynamical processes, but has yet to be explored for evolutionary optimization. We then shift our attention toward dynamic population structures, which have received markedly less attention than their static counterparts. We will discuss the strengths and limitations of extant techniques and present open theoretical and experimental questions and directions for future research. In particular, we will focus on the prospects of “active linking,” wherein edges are dynamically rewired according to the genotypic or phenotypic properties of individuals, or according to the success of prior inter-individual interactions.     

Extending the information delivery manual approach to identify information requirements for performance analysis of HVAC systems

Heating, Ventilation and Air-Conditioning (HVAC) systems account for more than 15% of the total energy consumption in the US. In order to improve the energy efficiency of HVAC systems, researchers have developed hundreds of algorithms to automatically analyze their performance. However, the complex information, such as configurations of HVAC systems, layouts and materials of building elements and dynamic data from the control systems, required by these algorithms inhibits the process of deploying them in real-world facilities. To address this challenge, we envision a framework that automatically integrates the required information items and provides them to the performance analysis algorithms for HVAC systems. This paper presents an approach to identify and document the information requirements from the publications that describe these algorithms. We extend the Information Delivery Manual (IDM) approach so that the identified information requirements can be mapped to multiple information sources that use various formats and schemas. This paper presents the extensions to the IDM approach and the results of using it to identify information requirements for performance analysis algorithms of HVAC systems.     

Foveation-based content adaptive root mean squared error for video quality assessment

Multimedia Tools and Applications - When the video is compressed and transmitted over heterogeneous networks, it is necessary to ensure the satisfying quality for the end user. Since human...     

A Bayesian paradox and its impact on the GUM approach to uncertainty

The paper presents ideas and observations about the use of the frequentist and the Bayesian approach to estimation and uncertainty. The merits and the pitfalls of the Bayesian approach, compared with the frequentist one, are illustrated using a simple example, which gives rise to an instructive paradox. The impact of the paradox on the GUM approach to uncertainty prescribed in Supplement 1 is highlighted and discussed.     

An Integrated System for UAV Control Using a Neural Network Implemented in a Prototyping Board

Modern aerospace vehicles are expected to have non-conventional flight envelopes and then, in order to operate in uncertain environments, they must guarantee a high level of robustness and adaptability. A Neural Network (NN) controller, with real-time learning capability, can be used in applications with manned or unmanned aerial vehicles. In this paper a novel real-time control system, based on a NN model, in order to control the trajectories of a hexacopter is proposed. The proposed NN is optimized by the analytical calculation of the embedding parameters. The paper shows a performance evaluation, through a real experimental testbed, of the proposed approach in terms of error measures and computation of the angular velocities of the hexacopter.     

Submicron machining and biomolecule immobilization on porous silicon by electron beam

Three-dimensional submicrometric structures and biomolecular patterns have been fabricated on a porous silicon film by an electron beam-based functionalization method. The immobilized proteins act as a passivation layer against material corrosion in aqueous solutions. The effects'' dependence on the main parameters of the process (i.e., the electron beam dose, the biomolecule concentration, and the incubation time) has been demonstrated.