Miracle-dz/UniFAR-FTUs huggingface dataset:
SFViz: interest-based friends exploration and recommendation in social networks

Friend recommendation is popular in social network services to help people make new friends and expand their networks. Friend recommendation is either based on topological structures of a social network, or derived from profile information of users. However, dynamically recommending friends by considering both social connections and a context of social connections (e.g., similar interest) in a way of visual exploration is not well supported by existing tools. In this paper, we propose a novel visual system, SFViz (Social Friends Visualization), to support users to explore and find friends interactively under a context of interest. Our approach leverages both semantic structure of activity data and topological structures in social networks. In SFViz, a hierarchical structure of social tags is generated to help users navigate through a network of interest. Multiscale and cross-scale aggregations of similarity among people are presented in the hierarchy to support users to seek potential friends. We report a case study using SFViz to explore the recommended friends based on people's tagging behaviors in a music community, Last.fm. The results indicate that our system can enhance users' awareness of their social networks under different interest contexts, and help users seek potential friends sharing similar interests in an interactive way.
From bytecode to JavaScript: the Js_of_ocaml compiler

We present the design and implementation of a compiler from OCaml bytecode to JavaScript. The compiler first translates the bytecode into a static single‐assignment intermediate representation on which optimizations are performed, before generating JavaScript. We believe that taking bytecode as an input instead of a high‐level language is a sensible choice. Virtual machines provide a very stable API. Such a compiler is thus easy to maintain. It is also convenient to use, and it can just be added to an existing installation of the development tools. Already‐compiled libraries can be used directly, with no need to reinstall anything. Finally, some virtual machines are the target of several languages. A bytecode to JavaScript compiler would make it possible to retarget all these languages to Web browsers at once. Copyright © 2013 John Wiley & Sons, Ltd.
Flow equation for supersymmetric quantum mechanics

We study supersymmetric quantum mechanics with the functional RG formulated in terms of an exact and manifestly off-shell supersymmetric flow equation for the effective action. We solve the flow equation nonperturbatively in a systematic super-covariant derivative expansion and concentrate on systems with unbroken supersymmetry. Already at next-to-leading order, the energy of the first excited state for convex potentials is accurately determined within a 1% error for a wide range of couplings including deeply nonperturbative regimes.
A Novel Role for Arabidopsis CBL1 in Affecting Plant Responses to Glucose and Gibberellin during Germination and Seedling Development

Glucose and phytohormones such as abscisic acid (ABA), ethylene, and gibberellin (GA) coordinately regulate germination and seedling development. However, there is still inadequate evidence to link their molecular roles in affecting plant responses. Calcium acts as a second messenger in a diverse range of signal transduction pathways. As calcium sensors unique to plants, calcineurin B-like (CBL) proteins are well known to modulate abiotic stress responses. In this study, it was found that CBL1 was induced by glucose in Arabidopsis. Loss-of-function mutant cbl1 exhibited hypersensitivity to glucose and paclobutrazol, a GA biosynthetic inhibitor. Several sugar-responsive and GA biosynthetic gene expressions were altered in the cbl1 mutant. CBL1 protein physically interacted with AKINβ1, the regulatory β subunit of the SnRK1 complex which has a central role in sugar signaling. Our results indicate a novel role for CBL1 in modulating responses to glucose and GA signals.
Trends in Fuzzy Statistics

After introducing and developing fuzzy set theory, a lot of studies have been done to combine statistical methods and fuzzy set theory. Thisworks, called fuzzy statistics, have been developed in some branches. In this article we review essential works on fuzzy estimation, fuzzy hypotheses testing, fuzzy regression, fuzzy Bayesian statistics, and some relevant fields.
Interference Reduction in Multi-Cell Massive MIMO Systems I: Large-Scale Fading Precoding and Decoding

A wireless massive MIMO system entails a large number (tens or hundreds) of base station antennas serving a much smaller number of users, with large gains in spectral-efficiency and energy-efficiency compared with conventional MIMO technology. Until recently it was believed that in multi-cellular massive MIMO system, even in the asymptotic regime, as the number of service antennas tends to infinity, the performance is limited by directed inter-cellular interference. This interference results from unavoidable re-use of reverse-link training sequences (pilot contamination) by users in different cells. We devise a new concept that leads to the effective elimination of inter-cell interference in massive MIMO systems. This is achieved by outer multi-cellular precoding, which we call Large-Scale Fading Precoding (LSFP). The main idea of LSFP is that each base station linearly combines messages aimed to users from different cells that re-use the same training sequence. Crucially, the combining coefficients depend only on the slow-fading coefficients between the users and the base stations. Each base station independently transmits its LSFP-combined symbols using conventional linear precoding that is based on estimated fast-fading coefficients. Further, we derive estimates for downlink and uplink SINRs and capacity lower bounds for the case of massive MIMO systems with LSFP and a finite number of base station antennas.
Do Institutions Affect Sustainability?

This paper shows a significant and causal positive relationship between good institutions and sustainability. Sustainability is measured by the indicator of adjusted net saving (ANS) and institutional quality by an average of six dimensions of governance. An instrumental variable is used to rule out reverse causality. Conducting the regression accordingly on the national savings rate yields a much weaker and smaller effect. This suggests that the saving of non-physical capital is influenced more strongly by institutional quality than that of physical capital. This further supports the explanation of the 'resource curse' by institutions.
Fluctuations of recentered maxima of discrete Gaussian Free Fields on a class of recurrent graphs

We provide conditions that ensure that the recentered maximum of the Gaussian free field on a sequence of graphs fluctuates at the same order as the field at the point of maximal variance. In particular, on a sequence of such graphs the recentered maximum is not tight, similarly to the situation in Z but in contrast with the situation in Z^2. We show that our conditions cover a large class of "fractal" graphs.
Marginal adaptation of class V composite restorations submitted to thermal and mechanical cycling

Objective: This study evaluated the effect of the margin location and an adhesive system on the marginal adaptation of composite restorations. Material and Methods: Class V cavities were prepared in bovine teeth with the gingival margin on the dentin and the incisal margin on the enamel. The cavities were restored with a micro-hybrid composite resin using an etch-and-rinse [Single Bond 2 (SB)] or a self-etching adhesive [Clearfil SE Bond (CL)]. After finishing and polishing the restorations, epoxy replicas were prepared. The marginal adaptation was analyzed using scanning electronic microscopy (SEM, 500 x magnification). The higher gap width in each margin was recorded (T0). After the first evaluation, the samples were submitted to thermal cycling (2,000 cycles of 5ºC±2ºC followed by 55ºC±2ºC - T1) and mechanical cycling (100,000 cycles of 50 kN and 2 Hz - T2). Replicas of samples were rebuilt after each cycling and analyzed under SEM. The data were submitted to Mann-Whitney, Wilcoxon and Friedman testing (a=0.05). Results: The SB presented higher gaps in the dentin than the enamel, while there was no difference between the substrate for the CL. In the dentin, the CL showed better marginal sealing than the SB. The opposite occurred in the enamel. There were no significant differences between the baseline, thermal and mechanical cycling for any experimental condition. Conclusions: The outcomes of the present study showed that the adhesive system and margin location have an important effect on the marginal adaptation of composite restorations.
Pythia: Diagnosing Performance Problems in Wide Area Providers

Performance problem diagnosis is a critical part of network operations in ISPs. Service providers typically deploy monitoring nodes at several vantage points in their network, to record end-to-end measurements of network performance. Network operators use these measurements offline; for example, to troubleshoot customer complaints. In this work, we leverage such monitoring infrastructure deployments in ISPs to build a system for near real time performance problem detection and root cause diagnosis. Our system works with wide area interdomain monitoring, unlike approaches that require data sources from network devices (SNMP, Netflow, router logs, table dumps, etc.). Operators can input operational and domain knowledge of performance problems to the system to add diagnosis functionality. We have deployed the system on existing monitoring infrastructure in the US, diagnosing over 300 inter-domain paths. We study the extent and nature of performance problems that manifest in edge and core networks on the Internet.
Design and Implementation of Coldfusion-Based Web Application Firewall

Based on the comprehensively analysis of the security threats to the Web applications, the Cold Fusion-based Web Application Firewall is presented, and it's implemented with CFML. The test results show that the firewall can effectively block various malicious attacks against the application layer, such as SQL injection, XSS, etc., and protect the Cold Fusion-based Web applications.
Auto White Balance Using the Coincidence of Chromaticity Histograms

This paper presents a simple and robust auto white balance algorithm using the coincidence of chromaticity histograms. After analyzing the relationship between the coincidence of the color histogram and color constancy, the overlap area of chromaticity histograms that keep chromaticity of color images but not the effect of luminance existing in the color histogram is employed to estimate the correct illuminant in scenes. When the overlap reaches the maximum, correspondingly the respective gain coefficients of color channels can be derived to achieve the white balance of the camera. Through numerous experiments and evaluations based on the processing of real world images, the proposed coincidence of chromaticity histograms algorithm achieves the outstanding performance comparing to other algorithms. Furthermore, the simplicity, easy implementation and robustness to the luminance make it flexibly apply to the vision system of the autonomous robot running outdoor.
Trade-offs in optimizing the cache deployments of CDNs

Content delivery networks (CDNs) deploy globally distributed systems of caches in a large number of autonomous systems (ASes). It is important for a CDN operator to satisfy the performance requirements of end users, while minimizing the cache deployment cost. In this paper, we study the cache deployment optimization (CaDeOp) problem of determining how much server, energy, and bandwidth resources to provision in each cache AS, i.e., each AS chosen for cache deployment. The CaDeOp objective is to minimize the total cost incurred by the CDN, subject to meeting the end-user performance requirements. We formulate the CaDeOp problem as a mixed integer program (MIP) and solve it for realistic AS-level topologies, traffic demands, and non-linear energy and bandwidth costs. We also evaluate the sensitivity of the results to our parametric assumptions. When the end-user performance requirements become more stringent, the CDN footprint rapidly expands, requiring cache deployments in additional ASes and geographical regions. Also, the CDN cost increases several times, with the cost balance shifting toward bandwidth and energy costs. On the other hand, the traffic distribution among the cache ASes stays relatively even, with the top 20% of the cache ASes serving around 30% of the overall traffic.
Adaptive predictive control using recurrent neural network identification

This paper presents a new adaptive predictive control algorithm which consists of an on-line process identification part and a predictive control strategy which is updated every time a process model change is identified. The identification method is based on recurrent neural network (RNN) nonlinear AutoRegressive with eXternal input (NARX) model derived from dynamic feedforward neural network by adding feedback connection between output and input layers. Two model-based predictive control strategies have been studied: the generalized predictive controller (GPC) and nonlinear adaptive model predictive controller (NAMPC). The neural network training and validation data are obtained from the open-loop simulation of a validated first principles plant model. The identified neural network (NN) model is validated using the following three different validation algorithms: (1) one-step ahead cross-correlation; (2) Akaike's final prediction error (AFPE) estimate; and (3) 5-step ahead prediction simulations. The algorithm has been applied to the temperature control of a fluidized bed furnace reactor of the steam deactivation unit of a fluid catalytic cracking (FCC) pilot plant used to evaluate catalyst performance. The validation results show that the RNN models the reactor to a high degree of accuracy. Simulation results show that the proposed NAMPC control strategy outperforms the GPC at the expense of extra computation time.
Warp assisted tumour and target volume visualisation in radiation therapy

This paper describes warp assisted tumour delineation from the images in a CT scan sequence, and the first algorithm to realistically close the tumour volume prior the automated generation of the larger planning target volume, on which a cancer patient's radiotherapy treatment is based. Space variant dilation, driven by box-guides indicating multiple expansion vectors in a single operation, is introduced. The algorithms were first tested in clinical trials studying dose escalated prostate cancer treatment. Results are presented to show that the techniques provide the capability to delineate and close a tumour volume in a manner that reflects natural asymmetries at the volume extrema and in a distance/distances that is/are under the control of the clinical user. Space variant dilation is shown to be practical using a minimum of knowledge concerning tumour motion and anatomical constraints.
Differentiation between two epilittoral species, Scutovertex arenocolus spec. nov. and Scutovertex pilosetosus Polderman (Acari: Oribatida) from different European coasts

Scutovertex arenocolus spec. nov. living in the sandy shore of the Baltic coast is described. Additionally, a closely related species, S. pilosetosus, occurring in marsh habitats of the North Sea coast, is redescribed in detail. Both species show a similar habitus. Scutovertex arenocolus differs from S. pilosetosus in the length of body, cusps and notogastral setae, in the ridge on mentum as well as in a different exochorion structure of the eggs. A morphometric analysis of 14 morphological characters confirmed distinctly shorter cusps and notogastral setae in S. arenocolus. Additionally, a principal component analysis performed with 17 morphological traits provided a clear separation of these two species and of S. minutus. The results of these analyses lead to the conclusion that earlier reports of S. minutus in the coastal zone of the Atlantic, the Baltic and the North Sea should be assigned to the one or the other of these two littoral species.
Effect of actin-binding protein on the sedimentation properties of actin

Actin and actin-binding protein (ABP) have recently been purified from human platelet cytoskeletons (S. Rosenberg, A. Stracher, and R.C. Lucas, 1981, J. Cell Biol. 91:201-211). Here, the effect of ABP on the sedimentation of actin was studied. When ABP was added to preformed F- actin filaments, it bound until a maximum ratio of 1:9 (ABP:actin, mol:mol) was reached. however, when actin was polymerized in the presence of ABP, two and a half times more ABP was able to bind to the actin- that is, every 3.4 actin monomers were now bound by an ABP dimer. ABP was not able to induce the sedimentation of actin under nonpolymerizing conditions but was able to reduce the time and concentration of actin required for sedimentation under slow polymerizing conditions. ABP, therefore, exerts its effect of G-actin by either nucleating polymerization or by cross-linking newly formed oligomers into a more sedimentable form.
Special correspondences and Chow traces of Landweber-Novikov operations

Abstract We prove that the function field of a variety which possesses a special correspondence in the sense of M. Rost preserves rationality of cycles of small codimensions. This fact was proven by Vishik in the case of quadrics and played the crucial role in his construction of fields with u-invariant 2 r + 1. The main technical tools are the algebraic cobordism of Levine-Morel, the generalised degree formula and the divisibility of Chow traces of certain Landweber-Novikov operations. As a direct application of our methods we prove the similar fact for all F 4-varieties.
Collaboration strategies and technological innovation: a contractual perspective of the relationship between firms and technological centers

In this paper, a theoretical framework for analyzing the selection of governance structures for implementing collaboration agreements between firms and Technological Centers is presented and empirically discussed. This framework includes Transaction Costs and Property Rights’ theoretical assumptions, though complemented with several proposals coming from the Transactional Value Theory. This last theory is used for adding some dynamism in the governance structure election. As empirical evidence of this theoretical explanation, we analyse four real experiences of collaboration between firms and one Technological Center. These experiences are aimed to represent the typology of relationships which Technological Centers usually face. Among others, a key interesting result is obtained: R&D collaboration activities do not need to always be organized through hierarchical solutions. In those cases where future expected benefits and/or reputation issues could play an important role, the traditional more static theories could not fully explain the selected governance structure for managing the R&D relationship. As a consequence, these results justify further research about the adequacy of the theoretical framework presented in this paper in other contexts, for example, R&D collaborations between firms and/or between Universities or Public Research Centers and firms.
Externalities in U . S . Manufacturing TFP A Spatial VAR Approach

This paper investigates the usefulness of the semi-parametric spatial vector autoregressive approach proposed by Chen and Conley in modelling the growth rates of Total Factor Productivity (TFP) for a large cross-section of U.S. manufacturing industries. The magnitude of the interactions of TFP’s across sectors is of great economic significance as it gives an indication of the importance of Marshallian externalities which are a necessary ingredients in many endogenous growth models. In the approach by Chen and Conley the magnitude of the effect of one sector has on the other sectors depends on the economic distance between them. Both the dependence of the coefficients of the VAR and of the covariances of the error terms on the distances between sectors is modelled in a semi-parametric way using cardinal B-splines. Irrespective whether distances are computed from factor shares or input-output tables, most of the interaction seems to be captured by the covariances whereas lagged TFP growth rates and/or lagged growth rates of capital intensities have only a negligible effect. JEL classification: C310, O410
A Reconfigurable Hebbian Eigenfilter for Neurophysiological Spike Train Analysis

The emergence of multi-electrode array enables the study of real-time neurophysiological activities across multiple regions of the brain. However, the real-time extracellular action potentials recorded on any electrode represent the simultaneous electrical activity of an unknown number of neurons which present a critical challenge to the accuracy of interpretation and identification of the neural circuitry in the subsequent analysis. In this paper, we present a principal component analysis approach utilizing Hebbian eigenfilter to identify the corresponding electrical activities of each neuron, namely spike sorting. The Hebbian eigenfilter greatly simplifies the computational complexity of eigen-projection. An efficient FPGA-based Hebbian eigenfilter is proposed. The performance, accuracy and power consumption of our Hebbian eigenfilter are thoroughly evaluated through synthetic spike trains. The proposal enables real-time spike sorting and analysis, and leads the way towards future motor and cognitive neuroprosthetics.
A Method to Design Distributed Harmonic Matching Networks

In this paper a closed-form synthesis of distributed networks for harmonic matching is presented. Taking into account the fundamental frequency and its second and third harmonics, all the possible circuital solutions are examined and the synthesis relationships for the optimum solution are inferred. Finally some matching network examples, designed according to the proposed approach, are presented
Correspondenceless Structure from Motion

We present a novel approach for the estimation of 3D-motion directly from two images using the Radon transform. The feasibility of any camera motion is computed by integrating over all feature pairs that satisfy the epipolar constraint. This integration is equivalent to taking the inner product of a similarity function on feature pairs with a Dirac function embedding the epipolar constraint. The maxima in this five dimensional motion space will correspond to compatible rigid motions. The main novelty is in the realization that the Radon transform is a filtering operator: If we assume that the similarity and Dirac functions are defined on spheres and the epipolar constraint is a group action of rotations on spheres, then the Radon transform is a correlation integral. We propose a new algorithm to compute this integral from the spherical Fourier transform of the similarity and Dirac functions. Generating the similarity function now becomes a preprocessing step which reduces the complexity of the Radon computation by a factor equal to the number of feature pairs processed. The strength of the algorithm is in avoiding a commitment to correspondences, thus being robust to erroneous feature detection, outliers, and multiple motions.
Big Data for Medical Image Analysis: A Performance Study

Big data systems can be used to facilitate powerful medical image analysis at scale. Understanding their behaviors in this context can lead to many benefits, ranging from superior infrastructure configurations to optimized parallel algorithm implementations. This paper is, to our knowledge, a first step towards developing such an understanding for state-of-the-art big data platforms. We characterize a representative medical image segmentation pipeline, detailing the per-stage CPU, memory, I/O reads and writes, and execution time patterns. This characterization has already helped us overcome a bottleneck persistently causing analysis to crash unexpectedly, and avoid poor architecture choices on storage and parallel execution.