Electrosynthesized CuMgAl Layered Double Hydroxides as New Catalysts for the Electrochemical Reduction of CO2

In this study, new nanostructured CuMgAl Layered Double Hydroxide (LDH) based materials are synthesized on a 4 cm² sized carbonaceous gas diffusion membrane. By means of microscopic and spectroscopic techniques, the catalysts are thoroughly investigated, revealing the presence of several species within the same material. By a one-step, reproducible potentiodynamic deposition it is possible to obtain a composite with an intimate contact between a ternary CuMgAl LDH and Cu⁰/Cu₂O species. The catalyst compositions are investigated by varying: the molar ratio between the total amount of bivalent cations and Al³⁺, the amount of loading, and the molar ratios among the three cations in the electrolyte. Each electrocatalyst has been evaluated based on the catalytic performances toward the electrochemical CO₂ reduction to CH₃COOH at −0.4 V versus reversible hydrogen electrode  in liquid phase. The optimized catalyst, that is, CuMgAl 2:1:1 LDH exhibits a productivity of 2.0 mmol_CH3COOH g_cat⁻¹ h⁻¹. This result shows the beneficial effects of combining a material like the LDHs, alkaline in nature, and thus with a great affinity to CO₂, with Cu⁰/Cu⁺ species, which couples the increase of carbon sources availability at the electrode with a redox mediator capable to convert CO₂ into a C₂ product.     

Sparsity-driven reconstruction for FDOT with anatomical priors

In this paper we propose a method based on (2, 1)-mixed-norm penalization for incorporating a structural prior in FDOT image reconstruction. The effect of (2, 1)-mixed-norm penalization is twofold: first, a sparsifying effect which isolates few anatomical regions where the fluorescent probe has accumulated, and second, a regularization effect inside the selected anatomical regions. After formulating the reconstruction in a variational framework, we analyze the resulting optimization problem and derive a practical numerical method tailored to (2, 1)-mixed-norm regularization. The proposed method includes as particular cases other sparsity promoting regularization methods such as l(1)-norm penalization and total variation penalization. Results on synthetic and experimental data are presented.     

An Example of Human-Centric Sensor Network: Be Responsible Platform

The paper addresses the Be Responsible platform, a representative example of human-centric sensing network which, relying on the Info-Communication and Internet of Things concepts, aims to improve the communication between citizens, on one side, and government authorities, on the other side, with the purpose of resolving various problems encountered in a modern society. A widespread network of human-centric smartphone devices and PCs has been used as a valuable source of data collected and processed in order to trigger adequate actions upon problem resolving. In this way, humans acting as sensor operators and data sources become a powerful factor in improving their society. The Be Responsible platform enables the people to report the irregularities in various aspects of their social life (grey economy, misuse of government vehicles, ecology, traffic), and hence to take active part in resolving them. It also promotes positive and responsible social and institutional behavior, which has to be nurtured in any society seeking progress. The number of submitted reports as well as the money collected from the fine revenues and subsequently invested in projects of social good, undoubtedly prove that what could not be achieved through years of traditional government-led policy approach, was achieved in months of citizen engagement.     

E-business technologies for xRM: Exploring the readiness of public broadcasters

This paper examines the possibilities of enhancing relationship management between public service broadcasters and their stakeholders by harnessing the potential of newest e-business technologies and concepts, such as: social media, digital and interactive TV, and mobile computing. In order to facilitate adoption of relationship management strategy, a framework for leveraging relationship management is proposed. Evaluation was performed within the e-business system of a public broadcaster. This empirical study explored the readiness and expected benefits of relationship management implementation. The research results have indicated that a public broadcaster could achieve a higher level of social responsibility, improve business sustainability, and empower communication and collaboration with all the stakeholders by using emerging technologies for relationship management activities.     

Detection of Structural Features in Biological Signals

In this article structures in biological signals are treated. The simpler—directly visible in the signals, which still demand serious methods and algorithms in the feature detection, similarity investigation and classification. The major actions in this domain are of geometric, thus simpler sort, though there are still hard problems related to simple situations. The other large class of less simple signals unsuitable for direct geometric or statistic approach, are signals with interesting frequency components and behavior, those suitable for spectroscopic analysis. Semantics of spectroscopy, spectroscopic structures and research demanded operations and transformations on spectra and time spectra are presented. The both classes of structures and related analysis methods and tools share a large common set of algorithms, all of which aiming to the full automatization. Some of the signal features present in the brain signal patterns are demonstrated, with the contexts relevant in BCI, brain computer interfaces. Mathematical representations, invariants and complete characterization of structures in broad variety of biological signals are in the central focus.     

Trapping and recombination processes via deep level T3 in semi-insulating gallium arsenide

Trapping and recombination of free carriers by deep level T₃ has been studied. Occupancy of the level by electrons and dynamics of its filling and emptying as a function of illumination with monoenergetic photons in 0.69–1.55 eV range has been monitored by the thermally stimulated currents method. We have found that level T₃ behaves more like a recombination center than like an ordinary electron trap. Besides trapping free electrons from conduction band, this trap can also communicate with valence band, trapping holes. The capture cross section for trapping a hole is estimated to be comparable or even larger than the capture cross section for trapping an electron. However, in many experimental conditions free electrons are generated more abundantly than free holes, and free carrier mobility and thermal velocity are both much higher for electrons than for holes. Therefore, electron trapping often prevails, so that this frequently detected defect, has been up to now most often perceived as a deep electron trap.