Miracle-dz/UniFAR-FTUs huggingface dataset:
Soft-X study of buried interfaces in stratified media

The performance of multilayer optics depends on the quality of the buried interfaces between materials, whose intermixing strongly affects their behavior. We present an experimental method to determine, in a non destructively way, the amount of material intermixing at interfaces of multilayer structures. The reflection mechanism is related to the build up in the multilayer of a standing wave field, whose peaks and the valleys move as a function both of wavelength and of incidence angle. Exploiting this fact it is possible to modulate the electric field inside the multilayer in order to have different parts of the multilayer structure excited at a different extent and in particular the buried interfaces regions. The excitation is directly proportional to the intensity of the electric field and to the concentration of a given element in the sample. The excitation can be detected with different techniques, f.i. electron core level photoemission, fluorescence, luminescence, total electron yield. The flexibility of the experimental apparatus of the BEAR beamline (Elettra Trieste, Italy) allowed us to study some important classes of layered structures in the soft X-ray energy range, using the above mentioned techniques together with the determination of the Bragg conditions through the measurement of the specular reflectivity. We demonstrate the possibility of obtaining quantitative information on the width of the intermixing region, strongly related to the interface roughness, through the comparison with a phenomenological model of the intermixing and a numerical simulation of the standing field inside the multilayer.
Automatic determination of text readability over textured backgrounds for augmented reality systems

This paper describes a pattern recognition approach to determine readability of text labels in augmented reality systems. In many augmented reality applications, one of the ways in which information is presented to the user is to place a text label over the area of interest. However, if this information is placed over very busy and textured backgrounds, this can affect the readability of the text. The goal of this work was to identify methods of quantitatively describing conditions under which such text would be readable or unreadable. We used texture properties and other visual features to determine if a text placed on a particular background would be readable or not. Based on these features, a supervised classifier was built that was trained using data collected front human subjects' judgment of text readability. Using a rather small training set of about 400 human evaluations over 50 heterogeneous textures the system is able to achieve a correct classification rate of over 85%.
Real-Time Document Image Classification Using Deep CNN and Extreme Learning Machines

This paper presents an approach for real-time training and testing for document image classification. In production environments, it is crucial to perform accurate and (time-)efficient training. Existing deep learning approaches for classifying documents do not meet these requirements, as they require much time for training and fine-tuning the deep architectures. Motivated from Computer Vision, we propose a two-stage approach. The first stage trains a deep network that works as feature extractor and in the second stage, Extreme Learning Machines (ELMs) are used for classification. The proposed approach outperforms all previously reported structural and deep learning based methods with a final accuracy of 83.24% on Tobacco-3482 dataset, leading to a relative error reduction of 25% when compared to a previous Convolutional Neural Network (CNN) based approach (DeepDocClassifier). More importantly, the training time of the ELM is only 1.176 seconds and the overall prediction time for 2,482 images is 3.066 seconds. As such, this novel approach makes deep learning-based document classification suitable for large-scale real-time applications.
Teaching software engineering and software project management: An integrated and practical approach

We present a practical approach for teaching two different courses of Software Engineering (SE) and Software Project Management (SPM) in an integrated way. The two courses are taught in the same semester, thus allowing to build mixed project teams composed of five-eight Bachelor's students (with development roles) and one or two Master's students (with management roles). The main goal of our approach is to simulate a real-life development scenario giving to the students the possibility to deal with issues arising from typical project situations, such as working in a team, organising the division of work, and coping with time pressure and strict deadlines.
A Class of Data-Center Network Models Offering Symmetry, Scalability, and Reliability

We propose a symmetrical scheme, by drawing results from group theory, and use it to build a new class of data center network models. The results are superior to current network models with respect to a number of performance criteria. Greater symmetry in networks is important, as it leads to simpler structure and more efficient communication algorithms. It also tends to produce better scalability and greater fault tolerance. Our models are general and are expected to find many applications, but they are particularly suitable for large-scale data-center networks.
GaN, AlGaN, HfO2 based radial heterostructure nanowires

Gallium nitride based core/shell nanowire heterostructures are promising components for UV optoelectronic nanodevices. A better understanding of their growth mechanisms is required to tailor the growth and the properties of these structures. We report an investigation of GaN-based radial nanowire heterostructures grown by Molecular Beam Epitaxy combined with Atomic Layer Deposition of HfO2 dielectric cladding. The structural quality of GaN nanowire samples coated with different materials, the elemental distribution along the nanowires' length, as well as the elemental incorporation mechanism are discussed.
Security in device-to-device communications: a survey

Device-to-device (D2D) communication is a promising technology for the next generation mobile communication networks (5G). Indeed, it is expected to allow high throughput, reduce communication delays and reduce energy consumption and traffic load. D2D technology will enhance the capacity and the performance of traditional cellular networks. Security issues must be considered in all types of communications, especially when it comes to wireless communication between devices involved in controlling critical infrastructures and/or dealing with personal data. The authors propose taxonomy based on the review of recent works which have addressed the security issues in D2D communications. This taxonomy is more practical since it gives, on the one hand, a better readability and a good understanding of all the works that have addressed the security issues in the literature, and on the other hand, a roadmap towards a global security solution that combines the best techniques and security solutions inherent to each layer: physical, MAC, network and application.
Customer service in the retention of mobile phone users in Nigeria

Customer service has received considerable attention in marketing literature. This paper attempts to find the relationship between customer service on customer retention in telecommunication industry in Nigeria. If retention is not managed, customer’s loyalty may be lost. This study examined the potential constructs in customer retention by investigating the chain of effects of retention from customer service, satisfaction, value and behavioural intention. The hypotheses are supported except that a higher level of customer satisfaction does not lead to customer loyalty.
A Novel Algorithm for EMG Signal Processing and Muscle Timing Measurement

This paper presents a new method for the automated processing of surface electromyography (SEMG) signals, particularly suited for the detection of muscle activation timing. The method has an intermediate level of complexity between simpler (but less performing) and more complex (but in general slower) methods, and is successfully used in the development of biomedical devices for rehabilitation carried out by our group. The method proposed here is based on a statistical approach for threshold computation that is implemented without the need of maximum voluntary contraction or relaxed state, usually required to overcome the difficulty in obtaining the threshold value. The method is compared with 10 popular automated standard methods using different types of simulated signals that approximate the behavior of real SEMG signals. Both the number of activations detected and the onset time measured are analyzed. The algorithm is then applied to real SEMG signals acquired from healthy subjects. The results are finally compared with the literature values. The results show that the proposed algorithm is the best performing method when both the number of activations and the activation timing are considered. In real applications, the algorithm gives the results compatible with the well-agreed literature data.
Causes of Sprawl: A Portrait from Space

We study the extent to which US urban development is sprawling and consider what determines differences in sprawl across space. Using remote-sensing data to track the evolution of land use on a grid of 8.7 billion 30x30 metre cells, we measure sprawl as the amount of undeveloped land surrounding an average urban dwelling. On this measure, while the extent of sprawl remained roughly unchanged between 1976 and 1992, it varied dramatically across metropolitan areas. Ground water availability, temperate climate, rugged terrain, decentralized employment, early public transport infrastructure, uncertainty about metropolitan growth, and unincorporated land in the urban fringe all increase sprawl.
A compact 8-element MIMO antenna system for 802.11ac WLAN applications

A compact 8-element MIMO antenna system which conforms to the new 802.11ac standards is designed for WLAN applications. The antenna operates in the 5 GHz band. The elements of the MIMO antenna system are patch antennas loaded with the CSRR for antenna miniaturization. The overall size of the MIMO antenna system is 100 × 50 × 0.8 mm3. The measurement results of the fabricated antenna are found to be in agreement with the simulation results of the design. The measurements show that the proposed MIMO antenna has a minimum bandwidth of 80 MHz and a minimum isolation of 10.95 dB between its antenna elements. The maximum gain for a single operating element of the proposed antenna is -0.16 dBi.
The One-to-One Constraint in Analogical Mapping and Inference

Theories of analogical reasoning have assumed that a 1-to-1 constraint discourages reasoners from mapping a single element in 1 analog to multiple elements in another. Empirical evidence suggests that reasoners sometimes appear to violate the one-to-one constraint when asked to generate mappings, yet virtually never violate it when asked to generate analogical inferences. However, few studies have examined analogical inferences based on nonisomorphic analogs, and their conclusions are suspect due to methodological problems. We sought to elicit mixed inferences that could result from combining information from 2 possible mappings. Participants generated 2-to-1 correspondences when asked for explicit mappings, but did not produce mixed inferences. Multiple correspondences appear to arise from multiple isomorphic mappings, rather than from a single homomorphic mapping.
Characterization of evaporated and sputtered thin Au layers on poly(ethylene terephtalate)

Gold layers were prepared on poly(ethylene terephtalate) substrate by diode sputtering and vacuum evaporation. The mean layer thickness was determined by atomic absorption spectroscopy. Sheet electrical resistance and reflection of electromagnetic waves were used for the characterization of layers. Surface morphology of the layers was determined using atomic force and scanning electron microscopy. While the sputtering was found to proceed with two different rates, the vacuum evaporation proceeds at a constant rate. Rapid decrease of the sheet resistance was observed during sputtering, depending on the layer thickness, in contrast to vacuum evaporation. This can be due to different mechanisms of the Au deposition. According to the measured reflection of electromagnetic waves, the layers prepared by both techniques, i.e., sputtering and vacuum evaporation, are discontinuous for thicknesses below 4 nm, continuous but heterogeneous for thickness from 4 to 10 nm, and continuous and homogeneous for thickness above10 nm. The morphology of the layers prepared by vacuum evaporation does not depend on the layer thickness. Rounded clusters are observed on the surface of the evaporated layers. The layers prepared by sputtering exhibit significantly different morphology with much smaller, pointed clusters. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 99:1698–1704, 2006
Patient Centered Healthcare Informatics

—The healthcare system is undergoing a transformation from reactive care to proactive and preventive care. Patients or health consumers are actively acquiring knowledge to manage their health and seeking supports from their peers in addition to receiving healthcare support from healthcare professionals. 74% of American adults use the internet, of which 80% have looked online for healthcare information [6]. With the popularity of social media, many health consumers are also exchanging informational and emotional support with peers who have similar health conditions or diseases. The large volume of health consumer contributed content provides valuable resources for healthcare informatics research. It is worth to note that the information in the health consumer contributed content is timelier than the traditional resources such as electronic health records, centralized reporting systems, and pharmaceutical databases because health consumers often discuss their concerns with peers before any of them are reported in the traditional resources [22]. In this article, we review a few important healthcare informatics research issues that are centered on the patient contributed content and concerns.
Q- and A-learning Methods for Estimating Optimal Dynamic Treatment Regimes

In clinical practice, physicians make a series of treatment decisions over the course of a patient's disease based on his/her baseline and evolving characteristics. A dynamic treatment regime is a set of sequential decision rules that operationalizes this process. Each rule corresponds to a decision point and dictates the next treatment action based on the accrued information. Using existing data, a key goal is estimating the optimal regime, that, if followed by the patient population, would yield the most favorable outcome on average. Q- and A-learning are two main approaches for this purpose. We provide a detailed account of these methods, study their performance, and illustrate them using data from a depression study.
Harnessing the Power of the Crowd to Increase Capacity for Data Science in the Social Sector

We present three case studies of organizations using a data science competition to answer a pressing question. The first is in education where a nonprofit that creates smart school budgets wanted to automatically tag budget line items. The second is in public health, where a low-cost, nonprofit women's health care provider wanted to understand the effect of demographic and behavioral questions on predicting which services a woman would need. The third and final example is in government innovation: using online restaurant reviews from Yelp, competitors built models to forecast which restaurants were most likely to have hygiene violations when visited by health inspectors. Finally, we reflect on the unique benefits of the open, public competition model.
Biochemical and functional analysis of the Borna disease virus G protein

The Borna disease virus (BDV) antigenome is comprised of five major open reading frames (ORFs). Products have been reported only for ORFs I, II, and III, encoding N (p40), P (p24/p23), and M (gp18), respectively. ORF IV predicts a 57-kDa protein with several potential glycosylation sites. Analysis of radiolabeled extracts from BDV-infected C6 cells and BHK-21 cells transfected with a Semliki Forest virus vector that contains ORF IV demonstrated the presence of a 94-kDa protein (G protein) which was sensitive to tunicamycin, endoglycosidase F/N-glycosidase, and endoglycosidase H but not to O-glycosidase. Sera from BDV-infected rats detected the G protein and had neutralization activity that was reduced following immunoadsorption with the G protein. Preincubation of cells with the G protein interfered with BDV infectivity. This effect was enhanced by treatment of the G protein with the exoglycosidase alpha-mannosidase and reduced after subsequent treatment with N-acetyl-beta-D-glucosaminidase. In concert these findings indicate that ORF IV encodes a 94-kDa N-linked glycoprotein with extensive high mannose- and/or hybrid-type oligosaccharide modifications. The presence of neutralization epitopes on the G protein and its capacity to interfere with infectivity suggest that the G protein is important for viral entry.
Highly reliable 0.18 /spl mu/m Au/WSi gate pseudomorphic HJFETs with individually grounded source finger vias

A highly reliable 0.18 /spl mu/m Au/WSi refractory gate pseudomorphic HJFET with individually grounded source finger vias has been developed for V-band MMIC applications. The HJFET exhibited an MTTF of 1.6E7 hours at a channel temperature of 130/spl deg/C. A three-stage amplifier MMIC has demonstrated state-of-the-art performance, generating 16 dBm output power with 25 dB small signal gain at 60 GHz band. This result demonstrates high potential of our MMIC technology.
Design, Manufacturing and Test of a High Lift Secondary Flight Control Surface with Shape Memory Alloy Post-Buckled Precompressed Actuators

The use of morphing components on aerospace structures can greatly increase the versatility of an aircraft. This paper presents the design, manufacturing and testing of a new kind of adaptive airfoil with actuation through Shape Memory Alloys (SMA). The developed adaptive flap system makes use of a novel actuator that employs SMA wires in an antagonistic arrangement with a Post-Buckled Precompressed (PBP) mechanism. SMA actuators are usually used in an antagonistic arrangement or are arranged to move structural components with linearly varying resistance levels similar to springs. Unfortunately, most of this strain energy is spent doing work on the passive structure rather than performing the task at hand, like moving a flight control surface or resisting air loads. A solution is the use of Post-Buckled Precompressed (PBP) actuators that are arranged so that the active elements do not waste energy fighting passive structural stiffnesses. One major problem with PBP actuators is that the low tensile strength of the piezoelectric elements can often result in tensile failure of the actuator on the convex face. A solution to this problem is the use of SMA as actuator material due to their tolerance of tensile stresses. The power consumption to hold deflections is reduced by approximately 20% with the Post-Buckled Precompressed mechanism. Conventional SMAs are essentially non-starters for many classes of aircraft due to the requirement of holding the flight control surfaces in a given position for extremely long times to trim the vehicle. For the reason that PBP actuators balance out air and structural loads, the steady-state load on the SMAs is essentially negligible, when properly designed. Simulations and experiments showed that the SMAPBP actuator shows tip rotations on the order of 45°, which is nearly triple the levels achieved by piezoelectric PBP actuators. The developed SMAPBP actuator was integrated in a NACA0012 airfoil with a flexible skin to carry out wind tunnel tests.
Experimental Approaches for Testing if Tolerance Curves Are Useful for Predicting Fitness in Fluctuating Environments

Most experimental studies on adaptation to stressful environments are performed under conditions that are typically rather constant and rarely ecologically relevant. Fluctuations in natural environmental conditions are ubiquitous and include for example variation in intensity and duration of temperature, droughts, parasite loads, and availability of nutrients, predators and competitors. The frequency and amplitude of many of these fluctuations are expected to increase with climate change. Tolerance curves are often used to describe fitness components across environmental gradients. Such curves can be obtained by assessing performance in a range of constant environmental conditions. In this perspective we shortly list theoretical and experimental evidence why results obtained under constant environmental conditions might be misleading for processes in nature and therefore may not be suitable for predicting fitness and future species distribution and abundance. We further suggest experimental avenues that can provide a better foundation for forecasts of the distribution of biota.
Elasto-plastic bond mechanics of embedded fiber optic sensors in concrete under uniaxial tension with strain localization

Brittleness of the glass core inside fiber optic sensors limits their practical usage, and therefore they are coated with low-modulus softer protective materials. Protective coatings absorb a portion of the strain, and hence part of the structural strain is sensed. The study reported here corrects for this error through development of a theoretical model to account for the loss of strain in the protective coating of optical fibers. The model considers the coating as an elasto-plastic material and formulates strain transfer coefficients for elastic, elasto-plastic and strain localization phases of coating deformations in strain localization in concrete. The theoretical findings were verified through laboratory experimentation. The experimental program involved fabrication of interferometric optical fiber sensors, embedding within mortar samples and tensile tests in a closed-loop servo-hydraulic testing machine. The elasto-plastic strain transfer coefficients were employed for correction of optical fiber sensor data and results were compared with those of conventional extensometers.
Detection and Tracking of a Moving Target Using SAR Images with the Particle Filter-Based Track-Before-Detect Algorithm

A novel approach to detecting and tracking a moving target using synthetic aperture radar (SAR) images is proposed in this paper. Achieved with the particle filter (PF) based track-before-detect (TBD) algorithm, the approach is capable of detecting and tracking the low signal-to-noise ratio (SNR) moving target with SAR systems, which the traditional track-after-detect (TAD) approach is inadequate for. By incorporating the signal model of the SAR moving target into the algorithm, the ambiguity in target azimuth position and radial velocity is resolved while tracking, which leads directly to the true estimation. With the sub-area substituted for the whole area to calculate the likelihood ratio and a pertinent choice of the number of particles, the computational efficiency is improved with little loss in the detection and tracking performance. The feasibility of the approach is validated and the performance is evaluated with Monte Carlo trials. It is demonstrated that the proposed approach is capable to detect and track a moving target with SNR as low as 7 dB, and outperforms the traditional TAD approach when the SNR is below 14 dB.