Miracle-dz/UniFAR-FTUs huggingface dataset:
Compressive Sensing for Spread Spectrum Receivers

With the advent of ubiquitous computing there are two design parameters of wireless communication devices that become very important: power efficiency and production cost. Compressive sensing enables the receiver in such devices to sample below the Shannon-Nyquist sampling rate, which may lead to a decrease in the two design parameters. This paper investigates the use of Compressive Sensing (CS) in a general Code Division Multiple Access (CDMA) receiver. We show that when using spread spectrum codes in the signal domain, the CS measurement matrix may be simplified. This measurement scheme, named Compressive Spread Spectrum (CSS), allows for a simple, effective receiver design. Furthermore, we numerically evaluate the proposed receiver in terms of bit error rate under different signal to noise ratio conditions and compare it with other receiver structures. These numerical experiments show that though the bit error rate performance is degraded by the subsampling in the CS-enabled receivers, this may be remedied by including quantization in the receiver model. We also study the computational complexity of the proposed receiver design under different sparsity and measurement ratios. Our work shows that it is possible to subsample a CDMA signal using CSS and that in one example the CSS receiver outperforms the classical receiver.
Cooperative based software clustering on dependency graphs

Software clustering involves the partitioning of software system components into clusters with the goal of obtaining optimum exterior and interior connectivity between the components. Research in this area has produced numerous algorithms with different methodologies and parameters. In this paper, we propose a novel ensemble approach that synthesizes a new solution from the outcomes of multiple constituent clustering algorithms. The main idea behind our cooperative approach was inherited from machine learning, as applied to document clustering, but has been modified for use in software clustering. The conceptual modifications include working with differing numbers of clusters produced by the input algorithms and using graph structures rather than feature vectors. The empirical modifications include experiments for selecting the optimal cluster merging criteria. Case studies using open source software systems show that forging cooperation between leading state-of-the-art algorithms produces better results than any one state-of-the-art algorithm considered.
3D Massive MIMO Systems: Modeling and Performance Analysis

Multiple-input-multiple-output (MIMO) systems of current LTE releases are capable of adaptation in the azimuth only. Recently, the trend is to enhance system performance by exploiting the channel's degrees of freedom in the elevation, which necessitates the characterization of 3D channels. We present an information-theoretic channel model for MIMO systems that supports the elevation dimension. The model is based on the principle of maximum entropy, which enables us to determine the distribution of the channel matrix consistent with the prior information on the angles. Based on this model, we provide analytical expression for the cumulative density function (CDF) of the mutual information (MI) for systems with a single receive and finite number of transmit antennas in the general signal-to-interference-plus-noise-ratio (SINR) regime. The result is extended to systems with finite receive antennas in the low SINR regime. A Gaussian approximation to the asymptotic behavior of MI distribution is derived for the large number of transmit antennas and paths regime. We corroborate our analysis with simulations that study the performance gains realizable through meticulous selection of the transmit antenna downtilt angles, confirming the potential of elevation beamforming to enhance system performance. The results are directly applicable to the analysis of 5G 3D-Massive MIMO-systems.
Independent component analysis applied to pulse oximetry in the estimation of the arterial oxygen saturation (SpO2) - a comparative study

We examine various independent component analysis (ICA) digital signal processing algorithms for estimating the arterial oxygen saturation (SpO2) as measured by a reflective pulse oximeter. The ICA algorithms examined are FastICA, Maximum Likelihood ICA (ICAML), Molgedey and Schuster ICA (ICAMS), and Mean Field ICA (ICAMF). The signal processing includes pre-processing bandpass filtering to eliminate noise, and post-processing by calculating the SpO2. The algorithms are compared to the commercial state-of-the-art algorithm Discrete Saturation Transform (DST) by Masimo Corporation. It is demonstrated that ICAMS and ICAMF perform up to 13% better than DST. PPG recordings are done with a reflective pulse oximetry sensor integrated in an Electronic Patch. This system is intended for patients with chronic heart and lung conditions.
Burst Loss Resilient Packetization of Video

In video transmission over packet-based networks, packet losses usually occur in bursts. In this paper, we present a novel packetization method for increasing the robustness of compressed video against bursty packet losses. The proposed method is based on creating a coding order of macroblocks so that the blocks that are close to each other in the coding order end up being far from each other in the frame. Experimental results indicate that the proposed method improves the quality of reconstructed frames under burst loss by several dB compared to conventional FMO techniques, and about 0.7 dB compared to the state-of-the-art method called Explicit Chessboard-Wipe (ECW).
PRECLINICAL STUDY: The effect of naltrexone on amphetamine‐induced conditioned place preference and locomotor behaviour in the rat

Whereas amphetamine and other psychostimulants primarily act on the dopamine system, there is also evidence that other neurotransmitter systems, such as the endogenous opioid system, modulate psychostimulant‐induced effects. Several studies have investigated the role of opioid antagonists on cocaine‐induced conditioned place preference (CPP), but there is limited information about the interaction with amphetamines. The aim of the present study was to investigate the effect of the opioid receptor antagonist, naltrexone (NTX) on the conditioning, expression and reinstatement of amphetamine‐induced place preference. In addition, the effect of NTX on locomotor behaviour was measured during all sessions. During training, animals were conditioned with amphetamine (2 mg/kg) to induce place preference. In order to extinguish the conditioned behaviour, animals received saline for 12 days. Reinstatement of CPP was induced by a priming dose of amphetamine (0.5 mg/kg). The interaction of NTX and amphetamine was evaluated using three paradigms of CPP: with NTX (vehicle, 0.3, 1.0 and 3.0 mg/kg) administered either 30 minutes prior to amphetamine conditioning, or 30 minutes before the expression, or 30 minutes before the amphetamine priming to induce reinstatement. Naltrexone had no effect on the conditioning, the expression or the reinstatement induced by a priming dose of amphetamine. Further, NTX by itself did not induce place preference or place aversion. In contrast, NTX significantly attenuated the locomotor response to a priming dose of amphetamine without affecting general locomotor behaviour. The results suggest differences in opioid modulation of amphetamine‐induced behaviours in the rat.
The Evolution of Intron Size in Amniotes: A Role for Powered Flight?

Intronic DNA is a major component of eukaryotic genes and genomes and can be subject to selective constraint and have functions in gene regulation. Intron size is of particular interest given that it is thought to be the target of a variety of evolutionary forces and has been suggested to be linked ultimately to various phenotypic traits, such as powered flight. Using whole-genome analyses and comparative approaches that account for phylogenetic nonindependence, we examined interspecific variation in intron size variation in three data sets encompassing from 12 to 30 amniotes genomes and allowing for different levels of genome coverage. In addition to confirming that intron size is negatively associated with intron position and correlates with genome size, we found that on average mammals have longer introns than birds and nonavian reptiles, a trend that is correlated with the proliferation of repetitive elements in mammals. Two independent comparisons between flying and nonflying sister groups both showed a reduction of intron size in volant species, supporting an association between powered flight, or possibly the high metabolic rates associated with flight, and reduced intron/genome size. Small intron size in volant lineages is less easily explained as a neutral consequence of large effective population size. In conclusion, we found that the evolution of intron size in amniotes appears to be non-neutral, is correlated with genome size, and is likely influenced by powered flight and associated high metabolic rates.
Estimating growth parameters for the Drosophila melanogaster protein interaction network by a network comparison method based on breadth-first search

Availability of large-scale network data for real systems is enabling mathematical and computational methods to systematically model the formation of the networks. Various growth models are proposed to reproduce the structures of the real-world networks. Evaluating how well a model fits the network data is an outstanding challenge, since the structures of networks that have tens of thousands of vertices and edges are highly complex. We here use a trace curve, which is produced by a breadth-first search processing on the network, to characterize the structure of network. Because the trace curve is shaped by both the local and global structure of the network, it can be used to tell the subtle difference between networks. By comparing the curves of model network and real network data, we evaluate the fit of model to the data. The evaluation of fit subsequently can be used to estimate the growth parameters for real network, which are key factors affecting the growth of real system. We illustrate the power of this approach by estimating growth parameters for the Drosophila melanogaster protein interaction network.
A fourth-generation MIMO-OFDM broadband wireless system: design, performance, and field trial results

Increasing demand for high-performance 4G broadband wireless is enabled by the use of multiple antennas at both base station and subscriber ends. Multiple antenna technologies enable high capacities suited for Internet and multimedia services, and also dramatically increase range and reliability. In this article we describe a multiple-input multiple-output OFDM wireless communication system, lab test results, and field test results obtained in San Jose, California. These are the first MIMO system field tests to establish the performance of MIMO communication systems. Increased capacity, coverage, and reliability are clearly evident from the test results presented in this article.
Fall detection in indoor environment with kinect sensor

Falls are one of the major risks of injury for elderly living alone at home. Computer vision-based systems offer a new, low-cost and promising solution for fall detection. This paper presents a new fall-detection tool, based on a commercial RGB-D camera. The proposed system is capable of accurately detecting several types of falls, performing a real time algorithm in order to determine whether a fall has occurred. The proposed approach is based on evaluating the contraction and the expansion speed of the width, height and depth of the 3D human bounding box, as well as its position in the space. Our solution requires no pre-knowledge of the scene (i.e. the recognition of the floor in the virtual environment) with the only constraint about the knowledge of the RGB-D camera position in the room. Moreover, the proposed approach is able to avoid false positive as: sitting, lying down, retrieve something from the floor. Experimental results qualitatively and quantitatively show the quality of the proposed approach in terms of both robustness and background and speed independence.
Soft Reputation-Based Secure Cooperative Spectrum Sensing

Cognitive Radios (CRs) sense the radio spectrum environment dynamically and automatically in order to find underutilized spectrum and then exploit it intelligently. In face of the challenging propagation environments characterized by shadowing and fading effects, cooperative spectrum sensing (CSS) has been proposed to perform reliable spectrum sensing by taking advantage of the spatial diversity in multi-user Cognitive radio networks. In CSS, each secondary user sends its sensing data to the combining node, which makes a decision on the presence of the primary signal. However, CSS are typically very vulnerable to attacks where malicious CRs falsify sensing data. To identify misbehaved CRs and alleviate their adverse effects on CSS performance, a secure CSS scheme based on soft reputation has been proposed in this letter. Contrary to existing reputation-based secure CSS schemes, where reputation of CRs is assigned artificially, reputation of CRs is calculated utilizing the statistics of primary band occupancy. Simulation demonstrates the effectiveness of the proposed scheme.
A Human-Centred Tangible approach to learning Computational Thinking

Computational Thinking has recently become a focus of many teaching and research domains; it encapsulates those thinking skills integral to solving complex problems using a computer, thus being widely applicable in our society. It is influencing research across many disciplines and also coming into the limelight of education, mostly thanks to public initiatives such as the Hour of Code. In this paper we present our arguments for promoting Computational Thinking in education through the Human-centred paradigm of Tangible End-User Development, namely by exploiting objects whose interactions with the physical environment are mapped to digital actions performed on the system. Received on 18 July 2016; accepted on 20 July 2016; published on 23 August 2016
Not all songbirds calibrate their magnetic compass from twilight cues: a telemetry study

SUMMARY Migratory birds are able to use the sun and associated polarised light patterns, stellar cues and the geomagnetic field for orientation. No general agreement has been reached regarding the hierarchy of orientation cues. Recent data from naturally migrating North American Catharus thrushes suggests that they calibrate geomagnetic information daily from twilight cues. Similar results have been shown in caged birds in a few studies but not confirmed in others. We report that free-flying European migrants, song thrushes Turdus philomelos, released after pre-exposure to a horizontally rotated magnetic field, do not recalibrate their magnetic compass from solar cues, but rather show a simple domination of either the magnetic or the stellar compass. We suggest that different songbird species possess different hierarchies of orientation cues, depending on the geographic and ecological challenges met by the migrants.
A role for the inositol kinase Ipk1 in ciliary beating and length maintenance

Cilia project from cells as membranous extensions, with microtubule structural cores assembling from basal bodies by intraflagellar transport (IFT). Here, we report a ciliary role for the inositol 1,3,4,5,6-pentakisphosphate 2-kinase (Ipk1) that generates inositol hexakisphosphate. In zebrafish embryos, reducing Ipk1 levels inhibited ciliary beating in Kupffer's vesicle and decreased ciliary length in the spinal canal, pronephric ducts, and Kupffer's vesicle. Electron microscopy showed that ciliary axonemal structures were not grossly altered. However, coincident knockdown of Ipk1 and IFT88 or IFT57 had synergistic perturbations. With GFP-Ipk1 enriched in centrosomes and basal bodies, we propose that Ipk1 plays a previously uncharacterized role in ciliary function.
The novel infrared target localization algorithm for free floating space robot

With regards to the complicated characteristic of outer space, the infrared target recognition system has been investigated for free floating space robot. A novel algorithm is proposed based on visual location method for free floating space robot. Firstly, we set an omnidirectional camera with fixed lens on the ceiling. Here, the free floating robot is moving on the platform. Especially, in order to reduce image noise, we fix an infrared filter in the lens. Then, we place a number of infrared-emitting diodes on the free floating space robot and the targets. Finally, we can get the accurate positions and angle information of the robot and the target according to the location of the infrared light. The experimental results prove that this approach presented in this paper is an effective method for target detection and static target capture for free floating space robot.
Local positioning services on IEEE 802.11 networks

This paper deals with localization services in IEEE 802.11 networks. The proposed solution processes the Time Of Arrival (TOA) of location packets sent by any Mobile Terminal, received by the Location Supporting Nodes (LSN) and the Location Support Server (LSS) that compose the location services architecture. A fully compatible IEEE 802.11 Localization Services protocol supporting data exchange related to both TOA measurement and processing is reported. - Simulation results show the method efficiency in both IEEE 802.11 PCF and DCF modes. Assessment of the maximum number of MTs for which location services can be provided is also reported. Since high localization accuracy requires large bandwidth, a broadband antenna for LSN and LSS was designed. The related results are reported in the second part of the paper. Antenna was tested by HP 8510 Network analyzer for the s-parameters, and by anechoic chamber for the radiation pattern and polarization purity. The antenna works at 5.0 GHz (centre frequency) in broadband mode and is matched on the wireless operating frequencies with a percentage more than 8% (1:1.5 VSWR).
Indexing the positions of continuously moving objects

The coming years will witness dramatic advances in wireless communications as well as positioning technologies. As a result, tracking the changing positions of objects capable of continuous movement is becoming increasingly feasible and necessary. The present paper proposes a novel, R*-tree based indexing technique that supports the efficient querying of the current and projected future positions of such moving objects. The technique is capable of indexing objects moving in one-, two-, and three-dimensional space. Update algorithms enable the index to accommodate a dynamic data set, where objects may appear and disappear, and where changes occur in the anticipated positions of existing objects. A comprehensive performance study is reported.
Need data for driver behaviour analysis? Presenting the public UAH-DriveSet

Driving analysis is a recent topic of interest due to the growing safety concerns in vehicles. However, the lack of publicly available driving data currently limits the progress on this field. Machine learning techniques could highly enhance research, but they rely on large amounts of data which are difficult and very costly to obtain through Naturalistic Driving Studies (NDSs), resulting in limited accessibility to the general research community. Additionally, the proliferation of smartphones has provided a cheap and easy-to-deploy platform for driver behavior sensing, but existing applications do not provide open access to their data. For these reasons, this paper presents the UAH-DriveSet, a public dataset that allows deep driving analysis by providing a large amount of data captured by our driving monitoring app DriveSafe. The application is run by 6 different drivers and vehicles, performing 3 different behaviors (normal, drowsy and aggressive) on two types of roads (motorway and secondary road), resulting in more than 500 minutes of naturalistic driving with its associated raw data and processed semantic information, together with the video recordings of the trips. This work also introduces a tool that helps to plot the data and display the trip videos simultaneously, in order to ease data analytics. The UAH-DriveSet is available at: http:// www.robesafe. com/personal/eduardo.romera/uah-driveset.
Plastic deformation of GaAs at low temperatures

Abstract Intrinsic GaAs single crystals were deformed under hydrostatic pressure at temperatures down to 130K. Slip lines indicate that, below 300 K, deformation occurs by ½ ⟨101⟩{111} slip with frequent cross-slip. Above 300 K the crystal is so brittle that no slip lines are observed and the critical resolved shear stress τ c falls steeply with increasing temperature. Below 300 K the temperature dependence of τ c is weak, resulting in a hump in the τ c−T curve at about 300 K, as found in InP at 420 K. In this region the activation volume is several b 3, b being the length of the Burgers vector, and the activation energy is about 35kT. Transmission electron microscopy of specimens deformed at low temperatures reveals long screw dislocations, which are narrowly or not at all dissociated. Semiquantitative analysis indicates that, at low temperatures, plastic deformation occurs by kink pair formation of non-dissociated shuffle screw dislocations.
Reduced Surface Expression of Epithelial E-Cadherin Evoked by Interferon-Gamma Is Fyn Kinase-Dependent

Interferon gamma (IFNγ) is an important regulatory cytokine that can exert a pro-inflammatory effect in the gut, where it has been shown to increase epithelial permeability via disruption of the tight junctions. Here we investigated the potential for IFNγ to regulate the adherens junction protein E-cadherin, an important mediator of normal epithelial tissue function, using the model T84 human colonic epithelial cell line. IFNγ (10 ng/ml) stimulated increased internalization of E-cadherin as assessed by immunofluorescence microscopy; internalization was reversed when cells were treated with PP1 (125 nM), a Src kinase-selective inhibitor. Immunoprecipitation studies demonstrated loss of E-cadherin from membrane fractions following IFNγ treatment and a corresponding increase in cytosolic E-cadherin and its binding partners, p120-catenin and beta-catenin: effects that were Src-kinase dependent. E-cadherin and p120-catenin phosphorylation was increased by IFNγ treatment and siRNA studies showed this was dependent upon the Src-kinase isoform Fyn. E-cadherin ubiquitinylation and subsequent proteasomal degradation stimulated by IFNγ was found to be dependent upon Fyn and the E-cadherin-selective ubiquitin ligase, Hakai. Use of Fyn and Hakai siRNA inhibited the internalization of E-cadherin as shown by immunoblotting and confocal fluorescence microscopy. Finally, IFNγ treatment resulted in a more fragile T84 cell monolayer with increased cell detachment in response to physical stress, which was prevented by PP1 and siRNA targeting Fyn or Hakai. Collectively, these results demonstrate a Fyn kinase-dependent mechanism through which IFNγ regulates E-cadherin stability and suggest a novel mechanism of disruption of epithelial cell contact, which could contribute to perturbed epithelial barrier function.