Mathematical model for the hemodynamic response to venous occlusion measured with near-infrared spectroscopy in the human forearm

We propose a mathematical model to describe the hemodynamic changes induced by a venous occlusion in a human limb. These hemodynamic changes, which include an increase in blood volume, a reduction in blood flow, and modifications to the oxygen saturation of hemoglobin, can all be measured noninvasively with near-infrared spectroscopy (NIRS). To test the model, we have performed NIRS measurements on the human forearm, specifically on the brachioradialis muscle, during venous occlusion induced by a pneumatic cuff inflated around the upper arm to pressures within the range 10-60 mmHg. We have found a good agreement between parameters measured by NIRS (total hemoglobin concentration and hemoglobin saturation) and the corresponding model parameters (capacitor voltage and arterial/capillary branch current). In particular, model and experiment indicate that the time constant for blood accumulation during venous occlusion (approximately 73-79 s) is much slower than the time constant for blood drainage following cuff release (approximately 5 s). These results indicate that this mathematical model can be a valuable analytical tool to characterize, optimize, and further develop diagnostic measurement schemes that use venous occlusion approaches.     

Criterion for signal extraction in underdetermined mixtures of bounded support

This work studies the problem of recovering a complex signal (source) from an underdetermined linear mixture of bounded sources. We assume some a priori information of the desired signal in the form of a training sequence and complete absence of knowledge from the other sources, except for their bounded character. The main contribution of this letter is the proposal of a bounded component analysis of the training error that tries to condense the relevant information of the observations in a linear estimate of the desired signal. This subspace can be later used for subsequent refined estimation of the signal of interest. Simulations corroborate the good performance of the proposed method in high SNR scenarios.     

Reversible Fragmentation and Self‐Assembling of Nematic Liquid Crystal Droplets on Functionalized Pyroelectric Substrates

Investigation on the behavior of nematic liquid crystals on functionalized polar dielectric crystal substrates is accomplished. Very interesting effects can be observed in maneuvering liquid crystal droplets on the substrate surface, driven by electric fields generated by pyroelectric effect. Reversible drops fragmentation and self‐assembling in different configurations can be achieved. The dynamics of the observed phenomena is studied and the repeatability of the process is full assessed.     

Self‐Assembled Conjugated Thiophene‐Based Rotaxane Architectures: Structural,Computational, and Spectroscopic Insights into Molecular Aggregation

A comparative study of the self‐assembly at a variety of surfaces of a dithiophene rotaxane 1 ?β‐CD and its corresponding dumbbell, 1, by means of atomic force microscopy (AFM) imaging and scanning tunneling microscopy (STM) imaging on the micrometer and nanometer scale, respectively. The dumbbell is found to have a greater propensity to form ordered supramolecular assemblies, as a result of π–π interactions between dithiophenes belonging to adjacent molecules, which are hindered in the rotaxane. The fine molecular structure determined by STM was compared to that obtained by molecular modelling. The optical properties of both rotaxane and dumbbell in the solid state were investigated by steady‐state and time‐resolved photoluminescence (PL) experiments on spin‐cast films and diluted solutions. The comparison between the optical features of the threaded and unthreaded systems reveals an effective role of encapsulation in reducing aggregation and exciton migration for the rotaxanes with respect to the dumbbells, thus leading to higher PL quantum efficiency and preserved single‐molecule photophysics for longer times after excitation in the threaded oligomers.     

Analysis of high voltage step-up nonisolated DC–DC boost converters

A high voltage step-up nonisolated DC–DC converter based on coupled inductors suitable to photovoltaic (PV) systems applications is proposed in this paper. Considering that numerous approaches exist to extend the voltage conversion ratio of DC–DC converters that do not use transformers, a detailed comparison is also presented among the proposed converter and other popular topologies such as the conventional boost converter and the quadratic boost converter. The qualitative analysis of the coupled-inductor-based topology is developed so that a design procedure can be obtained, from which an experimental prototype is implemented to validate the theoretical assumptions.     

Mining statistically significant associations for exploratory analysis of human sleep data.

We introduce a specialized association rule mining technique that can extract patterns from complex sleep data comprising polysomnographic recordings, clinical summaries, and sleep questionnaire responses. The rules mined can describe associations among temporally annotated events and questionnaire or summary data; e.g., the likelihood that an occurrence of a rapid eye movement (REM) sleep stage during the second 100 sleep epochs of the night is associated with moderate caffeine intake. We use chi2 analysis to ensure statistical significance of the mined rules at the level P < 0.05. Our results, obtained by mining sleep-related data from 242 human subjects, reveal clinically interesting associations among the polysomnographic and summary variables. Our experience suggests that association mining may also be useful for selection of variables prior to using logistic regression.     

Interoperability in semantic Web of Things: Design issues and solutions

The significant improvement in processing power, communication, energy consumption, and the size of computational devices has led to the emergence of the Internet of Things (IoT). IoT projects raise many challenges, such as the interoperability between IoT applications because of the high number of sensors, actuators, services, protocols, and data associated with these systems. Semantics solves this problem by using annotations that define the role of each IoT element and reduces the ambiguity of information exchanged between the devices. This work presents SWoTPAD, a semantic framework that helps in the development of IoT projects. The framework is designer oriented and provides a semantic language that is more user‐friendly than OWL‐S and WSML and allows the IoT designer to specify devices, services, environment, and requests. Following this, it makes use of these specifications and maps them for RESTful services. Additionally, it generates an automatic service composition engine that is able to combine services needed to handle complex user requests. We validated this approach with two case studies. The former concerns a residential security system and the latter, the cloud application deployment. The average time required for service discovery and automatic service composition corresponds to 72.9% of the service execution time in the case study 1 and 64.4% in the case study 2.     

Analysis of an Approximate Decorrelating Detector

In this paper an approximate decorrelating detector is analyzed on the basis of a first order approximation to the inverse crosscorrelation matrix of signature waveforms. The approximation is fairly accurate for systems with low crosscorrelations and is exact in the two-user synchronous case. We present an exact as well as approximate analysis of the bit-error-rate performance of this detector on a channel that is subject to flat fading, and also specifically for the case of random signature waveforms. The detector outperforms the conventional matched filter receiver in terms of BER. The approximate decorrelator (while not being near-far resistant like the decorrelating detector) is fairly robust to imperfections in power control. Power trade-off regions are identified which characterize the significant advantage that the approximate decorrelator provides over the matched filter receiver. The reduced complexity of the approximate decorrelator and performance gains over the conventional matched filter makes it a viable alternative for implementation in practical CDMA systems, in particular in those where the signature waveforms span many symbol intervals.     

Optimized Prototype Filter Based on the FRM Approach for Cosine-Modulated Filter Banks

A design procedure for frequency-response masking (FRM) prototype filters of cosine-modulated filter banks (CMFBs) is proposed. In the given method, we perform minimization of the maximum attenuation level in the filters stopband, subject to intersymbol interference (ISI) and intercarrier interference (ICI) constraints. For optimization, a quasi-Newton algorithm with line search is used, and we provide simplified analytical expressions to impose the interference constraints, which greatly reduce the computational complexity of the optimization procedure. The result is lower levels of ISI and ICI for a predetermined filter order, or a reduced filter complexity for given levels of interferences. It is then illustrated how the FRM-CMFB structure is suitable for implementing filter banks with a large number of bands, yielding sharp transition bands and small roll-off factors, which is an attractive feature for a wide range of practical applications.