Miracle-dz/UniFAR-FTUs huggingface dataset:
Vertical Electrical Conductivity of ZnO/GaN Multilayers for Application in Distributed Bragg Reflectors

We have demonstrated an electrically conductive ZnO/GaN multilayer structure using hybrid plasma-assisted molecular beam epitaxy. Electrical <inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula> characteristics were measured through the top three pairs of a six pair ZnO/GaN sample. The total measured resistance was dominated by lateral and contact resistances, setting an upper limit of <inline-formula> <tex-math notation="LaTeX">$\sim 10^{-4}\,\Omega \! \cdot \! \text {cm}^{2}$ </tex-math></inline-formula> for the vertical specific series resistance of the stack. A strong contribution to the low resistance is the cancellation of spontaneous and piezoelectric polarization that occurs in the in-plane strained ZnO/GaN sample, as shown by electrical simulations. In addition, the simulations show that the actual vertical resistance of the sample could in fact be three orders of magnitude lower and that ZnO/GaN structures with thicknesses fulfilling the Bragg condition should have similar resistance. Our results suggest that ZnO/GaN distributed Bragg reflectors (DBRs) are a promising alternative to pure III-nitride DBRs in GaN-based vertical-cavity surface-emitting lasers.
On the drivers of global grain price volatility: an empirical investigation

Several drivers may generate market instability, but the partial contribution of different factors is still debated. We investigate how market-based drivers influence the global price volatility of three major grains: wheat, corn, barley. We adopt a Seemingly Unrelated Regression Equations model, in order to investigate potential common patterns. We compare inter-annual, intra-annual, and global volatility, to conclude on short-run and long-run dynamics of markets instability. We quantify the negative relationship linking (temporal) arbitrage and grain price volatility and conclude on the effects of supply movements on price volatility.
Adaptive Detection in Distributed Networks Using Maximum Likelihood Detector

This letter describes a maximum likelihood distributed detector algorithm with a special initialization that yields an exponential decay rate on error probabilities in transient, using the adaptive diffusion least mean squares (LMS) algorithm in a distributed sensor network. The nodes that compose the network must decide between two concurrent hypotheses concerning the environment where they are inserted, using local measurements and shared estimates coming from their neighbors. It is shown analytically and by simulations that the exponential performance does not depend on the LMS step size, provided it is sufficiently small.
Assessing the vibrational response and robustness of electronic systems by dissolving time and length scale

This paper presents a methodology to holistically analyse the effects of vibrational loads on electronic systems. An equivalent multi degree-of-freedom (DOF) damped system discretizes the complex structure and sets up the equation of motion. After modal testing the damping and stiffness coefficients, a numerical finite element model (FEM) is developed to identify critical components based on the mass participation factor. Including the system vibration behaviour by means of the characteristic transfer functions, the critical components are linear sub-modelled in the frequency domain to minimize calculation times. The statistical stress configuration caused by normally distributed random vibration cycles reveals electrical devices prone to significant damage. The mechanical damage in terms of high cycle fatigue is quantified in a second hierarchic linear submodel that considers both transfer functions and stress configuration of the critical components. By Inverse Fast Fourier transforming this input load from frequency to the time domain, it finally enables non-linear material models in the device submodel and the calculation of cumulative damage.
Investigating the impact of the training data volume for robust speech recognition using multi-task learning

Dealing with speech corrupted by noise and reverberation is still an issue for automatic speech recognition. To address this, a solution that can be combined with multi-style learning consists of using multi-task learning, where the acoustic model is trained to solve one main task and at least one auxiliary task simultaneously. In noisy and reverberant environment using clean-speech features estimation as auxiliary task has proven its efficiency, while the main task is speech recognition. Still, recognizing speech in these degraded conditions is all the more difficult when the amount of available data during training is limited. Thus, in this paper, we evaluate robust speech recognition based on multi-task learning when the amount of training data is gradually reduced. We show that using multi-task learning improves recognition and more specifically, that its impact is even more significant if the amount of training data is decreasing (up to 12% relative improvement of the word error rate). All training and testing experiments are carried out on parts of the CHiME4 database.
Is there compelling evidence that schizophrenia long‐term treatment guidelines should be changed?

chotic relapse. There are, of course, factors that may predict a more successful discontinuation trial. In a recent review, several such factors were listed: lack of schizophrenia diagnosis, better premorbid social and occupational functioning, good social support, shorter duration of illness, and shorter duration of untreated psychosis. These factors may help identify the better candidates for discontinuation. Timing, as well, is an important component, as it appears that patients who achieve remission for three months in the first two years of illness have a better clinical prognosis. This better prognosis is felt by some to indicate a higher likelihood of tolerating dose reduction and discontinuation. We support the conclusions outlined in the paper by Correll et al, and we believe that the current literature undermines the clinical certainty of antipsychotic medications in the long-term treatment of schizophrenia. While not a certainty, long-term antipsychotic treatment is a very common outcome for people with schizophrenia. We encourage a sense of curiosity about the possibility of dose reduction and discontinuation in appropriate patients. This open-mindedness will strengthen the therapeutic bond between provider and patient, and might likely lead to better clinical outcomes. In her book The Center Cannot Hold, E.R. Saks, a Professor in the Gould School of Law at the University of Southern California, describes how experiencing a different sense of reality on and off medications was a revelation which led her to accept that she had a mental illness. She observed that the more she accepted her illness, the less the illness defined her.
Development of land surface albedo parameterization based on Moderate Resolution Imaging Spectroradiometer (MODIS) data

[1] A new dynamic-statistical parameterization of snow-free land surface albedo is developed using the Moderate Resolution Imaging Spectroradiometer (MODIS) products of broadband black-sky and white-sky reflectance and vegetation and the North American and Global Land Data Assimilation System (LDAS) outputs of soil moisture during 2000–2003. The dynamic component represents the predictable albedo dependences on solar zenith angle, surface soil moisture, fractional vegetation cover, leaf plus stem area index, and greenness, while the statistical part represents the correction for static effects that are specific to local surface characteristics. All parameters of the dynamic and statistical components are determined by solving nonlinear constrained optimization problems of a physically based conceptual model for the minimization of the bulk variances between simulations and observations. They all depend on direct beam or diffuse radiation and visible or near-infrared band. The dynamic parameters are also functions of land cover category, while the statistical factors are specific to geographic location. The new parameterization realistically represents surface albedo variations, including the mean, shape, and distribution, around each dependent parameter. For composites of all temporal and spatial samples of the same land cover category over North America, correlation coefficients between the dynamic component of the new parameterization and the MODIS data range from 0.39 to 0.88, while relative errors vary within 8–42%. The gross (i.e., integrated over all categories) correlations and errors are 0.57–0.71 and 17–26%, changing with direct beam or diffuse radiation and visible or near-infrared band. The static local correction results in a further reduction in relative errors, producing gross values of 11–21%. The new parameterization is a marked improvement over the existing albedo scheme of the state-of-the-art Common Land Model (CLM), which has correlation coefficients from −0.57 to 0.71 and relative errors of 18–140% for individual land cover categories, and gross values of 0.03–0.32 and 37–71%, respectively.
Building a Teaching and Learning Community: A Blended Approach to Providing Support

Creating an active teaching and learning community can be challenging but at Memorial University, a blended approach is proving to be effective. Through regular face-to-face group discussions, one-on-onecoaching sessions, and online sharing and support, anactive community of teachers and learners is being created in Process Engineering. This paper details a practical approach to engaging students and faculty in program development, encouraging dialogue about best-practices in teaching and learning, sharing resources, and providing support and mentorship.
Caching Joint Shortcut Routing to Improve Quality of Service for Information-Centric Networking

Hundreds of thousands of ubiquitous sensing (US) devices have provided an enormous number of data for Information-Centric Networking (ICN), which is an emerging network architecture that has the potential to solve a great variety of issues faced by the traditional network. A Caching Joint Shortcut Routing (CJSR) scheme is proposed in this paper to improve the Quality of service (QoS) for ICN. The CJSR scheme mainly has two innovations which are different from other in-network caching schemes: (1) Two routing shortcuts are set up to reduce the length of routing paths. Because of some inconvenient transmission processes, the routing paths of previous schemes are prolonged, and users can only request data from Data Centers (DCs) until the data have been uploaded from Data Producers (DPs) to DCs. Hence, the first kind of shortcut is built from DPs to users directly. This shortcut could release the burden of whole network and reduce delay. Moreover, in the second shortcut routing method, a Content Router (CR) which could yield shorter length of uploading routing path from DPs to DCs is chosen, and then data packets are uploaded through this chosen CR. In this method, the uploading path shares some segments with the pre-caching path, thus the overall length of routing paths is reduced. (2) The second innovation of the CJSR scheme is that a cooperative pre-caching mechanism is proposed so that QoS could have a further increase. Besides being used in downloading routing, the pre-caching mechanism can also be used when data packets are uploaded towards DCs. Combining uploading and downloading pre-caching, the cooperative pre-caching mechanism exhibits high performance in different situations. Furthermore, to address the scarcity of storage size, an algorithm that could make use of storage from idle CRs is proposed. After comparing the proposed scheme with five existing schemes via simulations, experiments results reveal that the CJSR scheme could reduce the total number of processed interest packets by 54.8%, enhance the cache hits of each CR and reduce the number of total hop counts by 51.6% and cut down the length of routing path for users to obtain their interested data by 28.6–85.7% compared with the traditional NDN scheme. Moreover, the length of uploading routing path could be decreased by 8.3–33.3%.
Predicting 'Non-scents': Rationale for a Chemosensory-based Biotic Ligand Model

The key aspects and features of the Biotic Ligand model (BLM) to predict acute metal toxicity by considering site-specific water quality and metal binding characteristics at a physiologically sensitive biotic ligand, which is typically the gills of fishes are discussed. However, certain analytical challenges remain, which, if overcome can make the BLM an amazing predictor.
Communication Mediated through Natural Language Generation in Big Data Environments: The Case of Nomao

Along with the development of big data, various Natural Language Generation systems (NLGs) have recently been developed by different companies. The aim of this paper is to propose a better understanding of how these systems are designed and used. We propose to study in details one of them which is the NLGs developed by the company Nomao. First, we show the development of this NLGs underlies strong economic stakes since the business model of Nomao partly depends on it. Then, thanks to an eye movement analysis conducted with 28 participants, we show that the texts generated by Nomao’s NLGs contain syntactic and semantic structures that are easy to read but lack socio-semantic coherence which would improve their understanding. From a scientific perspective, our research results highlight the importance of socio-semantic coherence in text-based communication produced by NLGs.
Oversegmenting Graphs

We propose a novel method to adapt a graph to image data. The method drives the nodes of the graph towards image features. The adaptation process naturally lends itself to a measure of feature saliency which can then be used to retain meaningful nodes and edges in the graph. From the adapted graph, we propose the computation of a dual graph, which inherits the saliency measure from the adapted graph, and whose edges run along image features hence producing an oversegmenting graph. This dual graph captures the structure of the underlying image, and therefore constitutes a sparse representation of the image features and their topology. The proposed method is computationally efficient and fully parallelisable. We propose two distance measures find image saliency along graph edges, and evaluate its performance on synthetic images and on natural images from publicly available databases. In both cases, the salient-most nodes of the graph achieve average boundary recall over 90%. We also provide a qualitative comparison with two related techniques: superpixel clustering, and variational image meshing, showing potential for a large number of applications.
Cooperative new flow handling scheme for wireless multi-hop software defined networks

This paper proposes a Cooperative New Flow Handling (CNFH) scheme for wireless SDN enabled massive Machine-type communications (mMTC) network which aims to reduce the overall control message volume towards the controller under flow table inconsistency condition. To achieve this goal, CNFH makes use of neighbouring devices' forwarding functionality to conduct a localized policy searching mechanism. Stochastic geometry is adopted this work to carry out a theoretical analysis while simulation results, from the other hand, demonstrate that CNFH has a better performance when the density of the MTC network is high.
What factors motivate junior doctors to engage as clinical tutors? A qualitative study

Objectives The study aimed to explore and identify factors motivating junior doctors to engage as long-term clinical tutors in undergraduate medical education. Methods In this qualitative study, twenty-seven participants were recruited among junior doctors attending preparatory tutor courses at the Sahlgrenska Academy, University of Gothenburg, and the Primary Healthcare system, West Sweden. They were asked to respond to open-ended questions and write a short account of their needs as clinical tutors for medical students. A qualitative content analysis was performed. Results A main theme emerged: “Let me develop my skills in a supportive workplace, provide feedback and merits, and I will continue tutoring”. Participants described suitable personality as fundamental, and the need to develop professional skills, both as clinical tutors and physicians. Tutor education was an important source of knowledge and stimulation. A workplace environment, supporting learning and the tutor’s role, was considered important, including having an adequate time frame. A clear and well-prepared assignment was regarded essential. Junior doctors requested feedback and merits in their work as long-term tutors. Clinical tutorship was considered an optional task. Conclusions In this exploratory study, motivating factors of junior doctors’ engagement as future long-term tutors were identified. It is important to form a process where junior doctors can build up professional competence as clinical tutors and physicians. To ensure a sustainable tutorship in the future, we suggest that universities and healthcare authorities acknowledge and further study these motivating factors.
(A Secure Data Management Framework based on ARM TrustZone for Cloud Storage Services)

Today, anyone can have multiple mobile devices like smart phones and tablet PCs, and also can handle variety of user data at any time, in any place. For efficiently sharing or synchronizing the user data across multiple devices, many people are using cloud storage services. Although cloud storages provide flexibility and scalability in storing data, security issues should be handled especially when mobile devices try to access data stored in cloud storage. Currently, typical cloud storage services offer data encryption for security purpose but we think such method is not secure enough. Because we recognized that managing encryption keys by software and identifying users by simple ID and password are main defectives of current cloud storage services. In this paper, we propose a secure data access method to cloud storage in mobile environment. Our framework supports hardware-based key management, attestation on the client software integrity, and secure key sharing across the multiple devices. To achieve these features, we implemented our prototype based on ARM TrustZone technology[10] and TPM emulator[1, 2] which is running on secure world of the TrustZone environment.
Concentration and penetration depth of H introduced into crystalline Si by hydrogenation methods used to fabricate solar cells

The hydrogenation of crystalline Si by methods used to passivate defects in Si solar cells has been studied by infrared spectroscopy. For these experiments, floating-zone Si that contained Pt impurities that act as traps for H was used as a model system in which H could be directly detected. In this model system, the concentration and indiffusion depth of H were determined for different hydrogenation treatments so that their effectiveness could be compared. The postdeposition annealing of a hydrogen-rich SiNx surface layer was found to introduce H into the Si bulk with a concentration of ∼1015cm−3 under the best conditions investigated here.
Augmented reality visualization for thoracoscopic spine surgery

We are developing an augmented reality (AR) image guidance system in which information derived from medical images is overlaid onto a video view of the patient. The centerpiece of the system is a head-mounted display custom fitted with two miniature color video cameras that capture the stereo view of the scene. Medical graphics is overlaid onto the video view and appears firmly anchored in the scene, without perceivable time lag or jitter. We have been testing the system for different clinical applications. In this paper we discuss minimally invasive thoracoscopic spine surgery as a promising new orthopedic application. In the standard approach, the thoracoscope - a rigid endoscope - provides visual feedback for the minimally invasive procedure of removing a damaged disc and fusing the two neighboring vertebrae. The navigation challenges are twofold. From a global perspective, the correct vertebrae on the spine have to be located with the inserted instruments. From a local perspective, the actual spine procedure has to be performed precisely. Visual feedback from the thoracoscope provides only limited support for both of these tasks. In the augmented reality approach, we give the surgeon additional anatomical context for the navigation. Before the surgery, we derive a model of the patient's anatomy from a CT scan, and during surgery we track the location of the surgical instruments in relation to patient and model. With this information, we can help the surgeon in both the global and local navigation, providing a global map and 3D information beyond the local 2D view of the thoracoscope. Augmented reality visualization is a particularly intuitive method of displaying this information to the surgeon. To adapt our augmented reality system to this application, we had to add an external optical tracking system, which works now in combination with our head-mounted tracking camera. The surgeon's feedback to the initial phantom experiments is very positive.
Motion Control Block Implementation for Driving Computing System

This paper presents motion control block implementation for driving computing system. The driving computing system provides recognition, decision making and control functions based on an integrated hardware platform for autonomous driving. The purpose of the driving computing system is autonomous driving in the urban environment, and various functions are required for this. The motion control block controls the behavior of the autonomous vehicle following the local path and target speed from motion planner in the driving computing system[1]. This block consists of a driving mode decision module, a lateral controller, a longitudinal controller and a driver intention decision module. For the autonomous driving in the urban environment, the lateral and longitudinal controllers of the motion control block are implemented and the driving mode can be switched by the driver operation. In order to verify the algorithm of motion control block, the experiment was conducted in the ETRI (Electronics and Telecommunications Research Institute) the results were confirmed.
Lintbebouwing : algemeen én Belgisch

Zo op het eerste gezicht is de 'woekerende' lintbebouwing in Belgie iets dat het land onderscheidt van Nederland. Vanuit Nederlands perspectief wordt het zelfs kenmerkend geacht voor de Belgische ruimtelijke (wan)toestand. Bij nadere beschouwing blijkt lintbebouwing echter een wereldwijd voorkomend fenomeen, dat meestal resulteert uit het specifieke samenspel van overheidsregulering en particuliere ontwikkeling. De overheid geeft de vrije hand aan marktwerking, zonder dat de markt of de overheid instaat voor structurele investeringen in infrastructuur en het openbaar domein. Bruno De Meulder legt uit hoe de lintbebouwing in Belgie tot stand komt.