Dye‐Doped Polyhedral Oligomeric Silsesquioxane (POSS)‐Modified Polymeric Matrices for Highly Efficient and Photostable Solid‐State Lasers

Here, the design, synthesis, and characterization of laser nanomaterials based on dye‐doped methyl methacrylate (MMA) crosslinked with octa(propyl‐methacrylate) polyhedral oligomeric silsesquioxane (8MMAPOSS) is reported in relation to their composition and structure. The influence of the silicon content on the laser action of the dye pyrromethene 567 (PM567) is analyzed in a systematic way by increasing the weight proportion of POSS from 1 to 50%. The influence of the inorganic network structure is studied by replacing the 8MMAPOSS comonomer by both the monofunctionalized heptaisobutyl‐methacryl‐POSS (1MMAPOSS), which defines the nanostructured linear network with the POSS cages appearing as pendant groups of the polymeric chains, and also by a new 8‐hydrogenated POSS incorporated as additive to the polymeric matrices. The new materials exhibit enhanced thermal, optical, and mechanical properties with respect to the pure organic polymers. The organization of the molecular units in these nanomaterials is studied through a structural analysis by solid‐state NMR. The domain size of the dispersed phase assures a homogeneous distribution of POSS into the polymer, thus, a continuous phase corresponding to the organic matrix incorporates these nanometer‐sized POSS crosslinkers at a molecular level, in agreement with the transparency of the samples. The silicon–oxygen core framework has to be covalently bonded into the polymer backbone instead of being a simple additive and both the silica content and crosslinked degree exhibit a critical influence on the laser action.     

Star-shaped hexaaryltriindoles small molecules: Tuning molecular properties towards solution processed organic light emitting devices

We present a series of differently substituted star-shaped hexaaryltriindoles with tunable light-emitting properties. The deep blue emission is unchanged by donor peripheral substituents while an increasing acceptor character produces a reduction of the optical gap, an increased Stokes shift and eventually leads to the appearance of a new electronic level and to the simultaneous deep blue (413 nm) and green (552 nm) emission in solution. Quenching by concentration increases with the acceptor character but is lower as the tendency of these compounds to aggregate is stronger. Solution processed thin films present optical and morphological qualities adequate for device fabrication and similar electronic structure compared to solutions with an emission range from 423 nm up to 657 nm (red), demonstrating the possibility of tuning the energy levels by chemical functionalization. We have fabricated and characterized single-layer solution processed organic light emitting diodes (OLED) to investigate the influence on transport and emission properties of the substituting species. We analyzed the I–V response using a single-carrier numerical model that includes injection barriers and non-uniform electric-field across the layer. As a result, we obtained the electric field dependence of the mobility for each device. Best results are obtained on the most electron rich derivative functionalized with six donor methoxy groups. This material shows the highest emission efficiency in solid state, due to aggregation-induced enhancement, and better transport properties with the highest mobility and a very low turn-on voltage of 2.8 V. The solution processed OLED devices produce stable deep blue (CIE coordinates (0.16, 0.16)) to white (CIE coordinates (0.33, 0.3)) emission with similar luminous efficiencies.     

Radiation Pattern of Wearable Antennas: A Statistical Analysis of the Influence of the Human Body

This paper explores a statistical approach for modelling antennas?? behaviour in the vicinity of the human body. The statistics of radiation patterns, i.e., average and standard deviation, have been calculated for Uniform and Rayleigh distance Distributions of the antenna to the body. The coupling between the body and the antenna, and the reduction of antenna efficiency, lead to a distortion of the radiation pattern, which depends on the distance as well as on the location on the body. A patch antenna operating at 2.45?GHz, on the head, chest, arm, and leg was simulated in computer simulation technology (CST), using a voxel model. Results show that the relative change of the average radiation pattern for an antenna located on the chest can reach 24?%. The study was complemented with measurements, showing that, in the area of interest for on-body communications, an average difference between CST and measurements of 0.9?dB is found which can be considered very good.     

A microcontroller-based portable electrocardiograph recorder

We describe a low cost portable Holter design that can be implemented with off-the-shelf components. The recorder is battery powered and includes a graphical display and keyboard. The recorder is capable of acquiring up to 48 hours of continuous electrocardiogram data at a sample rate of up to 250 Hz.     

Diagnosis of learner dropout based on learning styles for online distance learning

The amount of data generated by computer systems in Online Distance Learning (ODL) contains rich information. One example of this information we define as the Learner Learning Trail (LLT), which is the sequence of interactions between the students and the virtual environment. Another example is the Learner Learning Style (LLS), which is associated with the student behavior and choices during the learning process. This information can be used to identify learner behavior and learning style. We perceived, after the study of related literature, that the research field of learner diagnosis for ODL does not apply the conjoint use of LLT and LLS. In this article, we propose a model capable of integrating data generated from the behavior of students in ODL with cognitive aspects of them, such as their Learning Styles, by crossing LLT with LLS. We also propose the CPAD method (Collect, Preprocessing, Analysis, Diagnosis), which is implemented by collecting the raw data regarding learning activities, preprocessing the data into structured time sequences, analyzing the sequences regarding the learning styles and using this analysis to diagnose the learner behavior. We selected the dropout to investigate, once the dropout rate in ODL is a real problem in universities around the world. In addition, the dropout is a student decision which can be associated with previous students behaviors. We performed a study with 202 learners to evaluate if learning styles are capable of explaining aspects of the student behavior. The results suggest that Sequential/Global learning style dimension is more capable of explaining the dropout than the other dimensions. Also, we performed four classification experiments to verify how the dimensions of Felder-Silverman Learning Style Model influence the learner diagnosis. We perceived that the Sequential/Global dimension could provide a higher accuracy average with lower variation independently of the diagnosis technique.     

Superoleophilic Magnetic Iron Oxide Nanoparticles for Effective Hydrocarbon Removal from Water

Various hydrocarbons are efficiently extracted from water by using a new sorbent material based on covalently functionalized magnetic nanoparticles. The functionalization of the magnetite nanoparticles with a self‐assembled monolayer of hexadecylphosphonic acid renders the nanoparticles oleophilic and the magnetic nature of magnetite allows for simple extraction of the hydrocarbon‐soaked sorbent. The sorbent material is capable of extracting single contaminants such as alkanes and aromatics and complex hydrocarbon mixtures such as crude oils in high extraction rates of up to 14 times the sorbent volume. Experimental results are explained by molecular dynamics simulations on the adsorption of single components from a hydrocarbon‐water mixture to the alkylphosphonic acid layer on the nanoparticles. The core–shell sorbent material is highly stable and therefore, reusable over several successive extraction cycles without degradation. The extraction performance is determined at different water temperatures, different water sources, and different magnetic core materials and evaluated compared to heptadecanoic acid functionalized magnetite. The new sorbent material provides the opportunity for an efficient, reliable, inexpensive, and environmental friendly removal of hydrocarbons from water.     

Regularized signal reconstruction for level-crossing sampling using Slepian functions

In this paper, we propose a method for efficient signal reconstruction from non-uniformly spaced samples collected using level-crossing sampling. Level-crossing (LC) sampling captures samples whenever the signal crosses predetermined quantization levels. Thus the LC sampling is a signal-dependent, non-uniform sampling method. Without restriction on the distribution of the sampling times, the signal reconstruction from non-uniform samples becomes ill-posed. Finite-support and nearly band-limited signals are well approximated in a low-dimensional subspace with prolate spheroidal wave functions (PSWF) also known as Slepian functions. These functions have finite support in time and maximum energy concentration within a given bandwidth and as such are very appropriate to obtain a projection of those signals. However, depending on the LC quantization levels, whenever the LC samples are highly non-uniformly spaced obtaining the projection coefficients requires a Tikhonov regularized Slepian reconstruction. The performance of the proposed method is illustrated using smooth, bursty and chirp signals. Our reconstruction results compare favorably with reconstruction from LC-sampled signals using compressive sampling techniques.     

Weighted Hyperbolic DV-Hop Positioning Node Localization Algorithm in WSNs

The localization of nodes plays a fundamental role in Wireless Sensor and Actors Networks (WSAN) identifying geographically where an event occurred, which facilitates timely response to this action. This article presents a performance evaluation of multi-hop localization range-free algorithms used in WSAN, such as Distance Vector Hop (DV-Hop), Improved DV-Hop (IDV-Hop), and the Weighted DV-Hop (WDV-Hop). In addition, we propose a new localization algorithm, merging WDV-Hop, with the weighted hyperbolic localization algorithm (WH), which includes weights to the correlation matrix of the estimated distances between the node of interest (NOI) and the reference nodes (RN) in order to improve accuracy and precision. As performance metrics, the accuracy, precision, and computational complexity are evaluated. The algorithms are evaluated in three scenarios where all nodes are randomly distributed in a given area, varying the number of RNs, the density of nodes in the network, and radio coverage of the nodes. The results show that in networks with 100 nodes, WDV-Hop outperforms the DV-Hop and IDV-Hop even if the number of RNs is reduced to 10. Moreover, our proposal shows an improvement in terms of accuracy and precision at the cost of increased computational complexity, specifically in the algorithm execution time, but without affecting the hardware cost or power consumption.