Miracle-dz/UniFAR-FTUs huggingface dataset:
Discretizations of the Spectral Fractional Laplacian on General Domains with Dirichlet, Neumann, and Robin Boundary Conditions

In this work, we propose novel discretizations of the spectral fractional Laplacian on bounded domains based on the integral formulation of the operator via the heat-semigroup formalism. Specifically, we combine suitable quadrature formulas of the integral with a finite element method for the approximation of the solution of the corresponding heat equation. We derive two families of discretizations with order of convergence depending on the regularity of the domain and the function on which the spectral fractional Laplacian is acting. Our method does not require the computation of the eigenpairs of the Laplacian on the considered domain, can be implemented on possibly irregular bounded domains, and can naturally handle different types of boundary constraints. Various numerical simulations are provided to illustrate performance of the proposed method and support our theoretical results.
Phycochemical Constituents and Biological Activities of Fucus spp.

Seaweeds are known to be a good supply of key nutrients including carbohydrates, protein, minerals, polyunsaturated lipids, as well as several other health-promoting compounds capable of acting on a wide spectrum of disorders and/or diseases. While these marine macroalgae are deeply rooted in the East Asian culture and dietary habits, their major application in Western countries has been in the phycocolloid industry. This scenario has however been gradually changing, since seaweed consumption is becoming more common worldwide. Among the numerous edible seaweeds, members of the genus Fucus have a high nutritional value and are considered good sources of dietary fibers and minerals, especially iodine. Additionally, their wealth of bioactive compounds such as fucoidan, phlorotannins, fucoxanthin and others make them strong candidates for multiple therapeutic applications (e.g., antioxidant, anti-inflammatory, anti-tumor, anti-obesity, anti-coagulant, anti-diabetes and others). This review presents an overview of the nutritional and phytochemical composition of Fucus spp. , and their claimed biological activities, as well as the beneficial effects associated to their consumption. Furthermore, the use of Fucus seaweeds and/or their components as functional ingredients for formulation of novel and enhanced foods is also discussed.
An Estimate Sequence for Geodesically Convex Optimization

We propose a Riemannian version of Nesterov’s Accelerated Gradient algorithm (RAGD), and show that for geodesically smooth and strongly convex problems, within a neighborhood of the minimizer whose radius depends on the condition number as well as the sectional curvature of the manifold, RAGD converges to the minimizer with acceleration. Unlike the algorithm in (Liu et al., 2017) that requires the exact solution to a nonlinear equation which in turn may be intractable, our algorithm is constructive and computationally tractable1. Our proof exploits a new estimate sequence and a novel bound on the nonlinear metric distortion, both ideas may be of independent interest.
RGB-D Object-to-CAD Retrieval

Recent advances in consumer-grade depth sensors have enable the collection of massive real-world 3D objects. Together with the rise of deep learning, it brings great potential for large-scale 3D object retrieval. In this challenge, we aim to study and evaluate the performance of 3D object retrieval algorithms with RGB-D data. To support the study, we expanded the previous ObjectNN dataset [HTT ∗ 17] to include RGB-D objects from both SceneNN [HPN ∗ 16] and ScanNet [DCS ∗ 17], with the CAD models from ShapeNetSem [CFG ∗ 15]. Evaluation results show that while the RGB-D to CAD retrieval problem is indeed challenging due to incomplete RGB-D reconstructions, it can be addressed to a certain extent using deep learning techniques trained on multi-view 2D images or 3D point clouds. The best method in this track has a 82% retrieval accuracy.
3D printing and modeling of congenital heart defects: A technical review

Use of 3D printing technology is expanding in healthcare. One of the common applications is the creation of anatomical models of congenital heart defects (CHD) from medical image data. These patient‐specific models are being used for multiple purposes including visualization of anatomy, simulation of surgical procedures, patient education, and facilitating communication between clinical staff.
Design space exploration for PIM architectures in 3D-stacked memories

Scaling existing architectures to large-scale data-intensive applications is limited by energy and performance losses caused by off-chip memory communication and data movements in the cache hierarchy. Processing-in-Memory (PIM) has been recently revisited to address the issues of memory and power wall, mainly due to the maturity of 3D-stacking manufacturing technology and the increasing demand for bandwidth and parallel access in emerging data-centric applications. Recent studies have shown a wide variety of processing mechanisms to be placed in the logic layer of 3D-stacked memories, not to mention the already available 3D-stacked DRAMs, such as Micron's Hybrid Memory Cube (HMC). Nevertheless, a few studies compare PIM accelerators to each other and have made efforts to indicate the trade-offs between power, area, and performance. In this paper, we review different state-of-the-art 3D-stacked in-memory accelerators, and we analyze them considering important constraints regarding area and power due to critical embedded nature of PIM. Aiming to point in the direction of massive parallel PIM designs, we take the simplest design found in this survey, and we explore the architectural design space to meet the constraints imposed by HMC. Our results show that the most straightforward approach can provide the highest performance while consuming the lowest amount of area and power, which makes it the most suitable design found in this survey for an energy-efficient in-memory accelerator, whether it goes in High-Performance Computing or Embedded Systems. For instance, the outstanding point in the design space indicates that a performance density of 320 GBps/mm2 and a performance efficiency of 0.6 GBps/mW can be achieved in the best scenario, that is, when a massive parallel application reaches the peak bandwidth.
Guess Me if You Can: Acronym Disambiguation for Enterprises

Acronyms are abbreviations formed from the initial components of words or phrases. In enterprises, people often use acronyms to make communications more efficient. However, acronyms could be difficult to understand for people who are not familiar with the subject matter (new employees, etc.), thereby affecting productivity. To alleviate such troubles, we study how to automatically resolve the true meanings of acronyms in a given context. Acronym disambiguation for enterprises is challenging for several reasons. First, acronyms may be highly ambiguous since an acronym used in the enterprise could have multiple internal and external meanings. Second, there are usually no comprehensive knowledge bases such as Wikipedia available in enterprises. Finally, the system should be generic to work for any enterprise. In this work we propose an end-to-end framework to tackle all these challenges. The framework takes the enterprise corpus as input and produces a high-quality acronym disambiguation system as output. Our disambiguation models are trained via distant supervised learning, without requiring any manually labeled training examples. Therefore, our proposed framework can be deployed to any enterprise to support high-quality acronym disambiguation. Experimental results on real world data justified the effectiveness of our system.
C-JAE: 3 DOF Robotic Ankle Exoskeleton with Compatible Joint Axes

This paper proposes a three degrees of freedom (DOF) robotic ankle exoskeleton with compatible joint axes, named C-JAE. The device consists of three separate units to achieve triplanar motions. The plantarflexion-dorsiflexion and inversion-eversion are externally powered, whereas internal-external rotation is passively supported. C-JAE is capable of complying with the functional and ergonomic requirements of the biological ankle joint. This is achieved by accurately mapping exoskeleton axes of rotation with the oblique axes of rotation of talocrural and subtalar joints of ankle. All mechanisms including the drive units are located anterior to shank and foot segments to carry out robotic rehabilitation and/or to provide locomotion assistance for humans having mobility disorders. Control experiments were conducted to assess aptitude of C-JAE to carry out ankle rehabilitation exercises. The results verified potential benefits of the proposed design to generate desired movement patterns of daily activities while providing power-assistance.
A Retrospective Study of Intracranial Pressure in Head-Injured Patients Undergoing Decompressive Craniectomy: A Comparison of Hypertonic Saline and Mannitol

Objective: The impact of hypertonic saline (HTS) on the control of increased intracranial pressure (ICP) in head-injured patients undergoing decompressive craniectomy (DC) has yet to be established. The current retrospective study was conducted to compare the effect of HTS and mannitol on lowering the ICP burden of these patients. Methods: We reviewed data on patients who had sustained a traumatic brain injury (TBI) and were admitted to the First People's Hospital of Kunshan between January 1, 2012, and August 31, 2017. Patients who received only one type of hyperosmotic agent, 3% HTS or 20% mannitol, after DC were included. The daily ICP burden (h/day) and response to the hyperosmolar agent were used as primary outcome measures. The numbers of days in the intensive care unit and in the hospital, and the 2-weeks mortality rates were also compared between the groups. Results: The 30 patients who received 3% HTS only and the 30 who received 20% mannitol only were identified for approximate matching and additional data analyses. The demographic characteristics of the patients in the two groups were comparable, but the daily ICP burden was significantly lower in the HTS group than in the mannitol group (0.89 ± 1.02 h/day vs. 2.11 ± 2.95 h/day, respectively; P = 0.038). The slope of the reduction in ICP in response to a bolus dose at baseline was higher with HTS than with mannitol (P = 0.001). However, the between-group difference in the 2-weeks mortality rates was not statistically significant (2 [HTS] vs. 1 [mannitol]; P = 0.554). Conclusion: When used in equiosmolar doses, the reduction in the ICP of TBI patients achieved with 3% HTS was superior to that achieved with 20% mannitol after DC. However, this advantage did not seem to confer any additional benefit terms of short-term mortality.
Bitstream-based attacks against reconfigurable hardware

In den letzten drei Jahrzehnten haben sich FPGAs zu fortgeschrittenen re-programmierbaren Hardwarebausteinen entwickelt und wurden zu elementaren Komponenten fur zahlreiche Informations- und Kommunikationssysteme. SRAM-basierte FPGAs werden in Anwendungen wie der Luft- und Raumfahrt, dem Gesundheitswesen, dem Militarbereich, der Automobilindustrie und in Computernetzwerken sowie Datenzentren genutzt. Viele Anwendungen sind sicherheitskritisch und benotigen deshalb kryptographische Operationen beispielsweise zur Generierung von Zufallszahlen, zum Schlusselaustausch oder zur Verschlusselung von Daten. In der Praxis werden kryptographische Schaltkreise durch proprietare Bitstreams kodiert, welche fur Angreifer haufig zuganglich sind, da diese extern uber einen Konfigurationsbus ubertragen und somit abgefangen bzw. ausgelesen werden konnen. Diese Arbeit zeigt auf, dass es einem Angreifer moglich ist kryptographische Hardwarekonfigurationen durch Bitstreammanipulationen zu kompromittieren.
A scheduling model for workflows on grids and clouds

This paper presents a set of comparisons of the performance of a bi-criteria scheduling algorithm for Workflows with Quality of Service (QoS) support. This work serves as basis to implement a bi-criteria hybrid scheduling algorithm for workflows with QoS support, aiming to optimize the criteria chosen by the users and based on the priority ordering and relaxation specified by them. Analyzing the comparisons and obtained results, indicates a performance improvement when adopting the model proposed in this paper.
The social inequalities of Internet access, its use, and the impact on children’s academic performance: Evidence from a longitudinal study in Switzerland

This longitudinal study explores differences in Internet access and use among school-aged children in Italian-speaking Switzerland and whether and how these differences contribute to inequalities in academic performance. Applying multilevel structural equation modeling with two-wave original survey data from 843 students, their parents, as well as students’ end-term school grades, we show that a family’s socio-economic status indirectly affects children’s school grades as lower parental income leads children to use the Internet more frequently for entertainment and online communication purposes. This form of Internet use also increases as children have more personal digital media devices. As children’s increased use of the Internet for entertainment and online communication worsens their academic performance, our results suggest that social inequalities due to children’s socio-economic status are reinforced by a second-order digital divide. We discuss potential reasons for our findings as well as their implications and recommendations for possible interventions.
Comparative analysis of soft-error detection strategies: a case study with iterative methods

Undetected soft errors caused by transient bit flips can lead to silent data corruption (SDC), an undesirable outcome where invalid results pass for valid ones. This has motivated the design of soft error detectors to minimize SDCs. However, the detectors have been studied under different contexts, making comparative evaluation difficult. In this paper, we present the first comprehensive evaluation of four online soft error detection techniques in detecting the adverse impact of soft errors on iterative methods. We observe that, across five iterative methods, the detectors studied achieve high but not perfect detection rates. To understand the potential for improved detection, we evaluate a machine-learning based detector that takes as features that are the runtime features observed by the individual detectors to arrive at their conclusions. Our evaluation demonstrates improved but still far from perfect detection accuracy for the machine learning based detectors. This extensive evaluation demonstrates the need for designing error detectors to handle the evolutionary behavior exhibited by iterative solvers.
Zika virus infects human testicular tissue and germ cells

Zika virus (ZIKV) is a teratogenic mosquito-borne flavivirus that can be sexually transmitted from man to woman. The finding of high viral loads and prolonged viral shedding in semen suggests that ZIKV replicates within the human male genital tract, but its target organs are unknown. Using ex vivo infection of organotypic cultures, we demonstrated here that ZIKV replicates in human testicular tissue and infects a broad range of cell types, including germ cells, which we also identified as infected in semen from ZIKV-infected donors. ZIKV had no major deleterious effect on the morphology and hormonal production of the human testis explants. Infection induced a broad antiviral response but no IFN upregulation and minimal proinflammatory response in testis explants, with no cytopathic effect. Finally, we studied ZIKV infection in mouse testis and compared it to human infection. This study provides key insights into how ZIKV may persist in semen and alter semen parameters, as well as a valuable tool for testing antiviral agents.
From Placebo to Panacea: Studying the Diffusion of IT Management Techniques with Ambiguous Efficiencies: The Case of Capability Maturity Model

In light of the inherent shortcomings of single-perspective approaches in IT diffusion research, in this paper, we develop a multi-perspective framework for studying the diffusion of IT management techniques. The framework is then applied to explain the diffusion of capability maturity model (CMM). This research contributes to information systems theory by (a) illustrating how several different theoretical perspectives (i.e., forced-selection, efficient choice, fashion, and fad) can be used to explain an IT management innovation diffusion; (b) identifying the specific limitations of each perspective; and (c) demonstrating how these perspectives can be reconciled and yield a holistic understanding of the diffusion trajectory. Building on 20+ years of CMM research, the propositions of this paper shed more light on the underlying dynamics driving the adoption decision among software vendors, and will inform IS scholars and practitioners about the types of actions that can foster the dissemination of emerging IT management techniques.
Overview on Fault Tolerance Strategies of Composite Service in Service Computing

In order to build highly reliable composite service via Service Oriented Architecture (SOA) in the Mobile Fog Computing environment, various fault tolerance strategies have been widely studied and got notable achievements. In this paper, we provide a comprehensive overview of key fault tolerance strategies. Firstly, fault tolerance strategies are categorized into static and dynamic fault tolerance according to the phase of their adoption. Secondly, we review various static fault tolerance strategies. Then, dynamic fault tolerance implementation mechanisms are analyzed. Finally, main challenges confronted by fault tolerance for composite service are reviewed.
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding

In this paper, we introduce DICOD, a convolutional sparse coding algorithm which builds shift invariant representations for long signals. This algorithm is designed to run in a distributed setting, with local message passing, making it communication efﬁcient. It is based on coordinate descent and uses locally greedy updates which accelerate the resolution compared to greedy co-ordinate selection. We prove the convergence of this algorithm and highlight its computational speed-up which is super-linear in the number of cores used. We also provide empirical evidence for the acceleration properties of our algorithm compared to state-of-the-art methods.
Semilinearity of Families of Languages

Techniques are developed for creating new and general language families of only semilinear languages, and for showing families only contain semilinear languages. It is shown that for language families [Formula: see text] that are semilinear full trios, the smallest full AFL containing [Formula: see text] that is also closed under intersection with languages in [Formula: see text] (where [Formula: see text] is the family of languages accepted by [Formula: see text]s augmented with reversal-bounded counters), is also semilinear. If these closure properties are effective, this also immediately implies decidability of membership, emptiness, and infiniteness for these general families. From the general techniques, new grammar systems are given that are extensions of well-known families of semilinear full trios, whereby it is implied that these extensions must only describe semilinear languages. This also implies positive decidability properties for the new systems. Some characterizations of the new families are also given.
Robust video tracking algorithm: a multi-feature fusion approach

This study proposes a novel robust video tracking algorithm consists of target detection, multi-feature fusion, and extended Camshift. Firstly, a novel target detection method that integrates Canny edge operator, three-frame difference, and improved Gaussian mixture model (IGMM)-based background modelling is provided to detect targets. The IGMM-based background modelling divides video frames into meshes to avoid pixel-wise processing. In addition, the output of the target detection is utilised to initialise the IGMM and to accelerate the convergence of iterations. Secondly, low-dimensional regional covariance matrices are introduced to describe video targets by fusing multiple features like pixel location, colour index, rotation and scale invariant features as well as uniform local binary patterns, and directional derivatives. Thirdly, an extended Camshift based on adaptive kernel bandwidth and robust H ∞ state estimation is proposed to predict the states of fast moving targets and to reduce the mean shift iterations. Finally, the effectiveness of the proposed tracking algorithm is demonstrated via experiments.
Hierarchical Beamforming in CRAN Using Random Matrix Theory

In this paper, we propose a hierarchical beamforming approach for the downlink of a multicellular multiuser system with cloud radio access network (CRAN) which requires reduced fronthaul transmissions while benefiting from the centralized functionality of the cloud. We design the hierarchical beamforming as a concatenation of two beamformers. The first one is called inner beamformer and it is designed at the base station (BS) based on the instantaneous channel state information (CSI) of its own users. For this beamformer, the BSs apply regularized zero-forcing (RZF). The second one is called outer beamformer and it is defined at the cloud based on the global but only statistical CSI. All outer beamformers are designed together at the cloud to allow coordination among the BSs. This hierarchical approach provides a combination of distributed and centralized precoding and so it manages the intra- cell as well as the inter-cell interference. Because the cloud has only statistical channel knowledge, we apply random matrix theory to obtain deterministic approximations of the useful power, intra-cell and inter-cell interference power at every user. These approximations are closed-form expressions and allow the cloud to optimize the outer beamformers for diverse objectives. In this work, we propose a low complexity iterative outer beamformer design based on block diagonalization which maximizes the system sum rate. Simulations show that the deterministic approximations are tight and that the proposed hierarchical beamforming achieves a higher sum rate compared to the conventional distributed RZF.
Optimizing Quality of Experience of Free-Viewpoint Video Streaming with Markov Decision Process

Free-viewpoint video (FVV) streaming is an emerging type of multimedia service that provides unprecedented interactivity for users to explore different scenes at different angles. Compared with traditional 2D video, delivering FVV is much more challenging because the uncertainty of view switching together with bandwidth variation may cause frequent playback interruptions. In this paper, we present the first stochastic optimization on the quality of experience (QoE) of FVV streaming that consists of two key components: video quality and interruption time. The bandwidth dynamics and the view switching are captured by different finite-state Markov processes, respectively. We formulate a novel Markov decision process (MDP) model where the state as well as its transition incorporates the view and the utility considers the quality of watching other than downloaded chunks. A policy iteration approach is adopted to obtain the optimal chunk selection strategy. Extensive simulations manifest that our approach outperforms the bandwidth based counterpart in terms of average bitrate and number of interruptions.