Miracle-dz/UniFAR-FTUs huggingface dataset:
3D animation creation using space canvases for free-hand drawing

In this paper we present a novel 3D animation system using a set of easily manipulable space canvases that support free-hand drawing. Our aim is to support the traditional free-hand drawing while improving the functionality by imitating the 3D animation in terms of free-viewing and free animation. The system design emphasis is on the feeling of "what you see is what you get". In our system a user is allowed to create planar and curved canvases and place them in 3D space with six degrees of freedom. Free-hand strokes are drawn on each canvas by using any of a user's favorite input device; a mouse, a digital pen, etc. Various canvases organized in space form a scene and the animation key frames of those canvases and strokes can be recorded hierarchically to represent different levels of movement in the scene. The camera's movement is recorded when a user tunes the viewing parameters and chooses to add a key frame in the time line for the camera. The system is both intuitive by utilizing the advantage of 2D freehand drawing and has the capability of 3D manipulation of strokes, canvases and a camera without requiring the user to have knowledge of 3D graphics and animation. We demonstrate the usability and efficiency of our system by describing the creation process of several short animation movies.
SAWM: a tool for secure and authenticated web metering

The aim of a metering system is the accurate measure of the number of accesses to a Web page in order to have feedback on the effectiveness of the advertising on the net. At the present, there are no standard means to measure the exposure of Web pages as well as the impact of online advertising campaigns. Indeed "traditional" metering techniques are afflicted by hit inflation and hit shaving attacks. In this paper we propose a framework to accurately count the number of visits to a Web site relying on cryptographic primitives. In this way it is possible to avoid cheating by any of the agents in such a framework. Furthermore, a viable implementation of a tool to securely monitor a Web site is discussed.
Correction to A note on the Entscheidungsproblem

In A note on the Entscheidungsproblem the author gave a proof of the unsolvability of the general case of the Entscheidungsproblem of the engere Funktionenkalkül. This proof, however, contains an error, in order to correct which it is necessary to modify the “additional axioms” of the system L so that they contain no free variables (either free individual variables or free propositional function variables). The additional axioms of L other than x=y→[F(x)→F(y)] contain no free propositional function variables, and hence it is sufficient to replace each one by an expression obtained from it by quantifying all the individual variables by means of universal quantifiers initially placed—thus, in particular, x = x is replaced by (x)[x=x]. Moreover the axiom x=y→[F(x)→F(y)] may be replaced by the following set of axioms: and similar axioms for each of the functions b1, b2, …, bk.
smedinx-11 is a planarian stem cell gap junction gene required for regeneration and homeostasis

The largely unknown mechanisms that regulate adult stem cells probably involve signals from neighboring differentiated cells. Gap junction channels providing direct cell-cell communication via small molecules are a crucial component of morphogenesis and normal physiology. However, no specific gap junction protein has yet been functionally linked to adult/somatic stem cell behavior in vivo or to organ regeneration. We report the identification and characterization of smedinx-11 - an innexin gap junction channel gene expressed in the adult stem cells (neoblasts) of the planarian Schmidtea mediterranea. smedinx-11 RNAi treatment inhibits regeneration and abrogates neoblast maintenance. Moreover, smedinx-11 expression is enriched in an irradiation-sensitive subpopulation (`X2') and is required for proper expression of other stem cell-specific markers. Analyses of the smedinx-11 downregulation phenotype revealed a striking anterior-posterior neoblast gradient. Our data demonstrate a novel role for gap junction proteins and suggest gap junction-mediated signaling as a new and tractable control point for adult, somatic stem cell regulation.
AODV with Source Route Accumulation for improved Routing in WiMAX

Worldwide Interoperability for Microwave Access (WiMAX) is a technology that bridges the gap between fixed and mobile access and offer the same subscriber experience for fixed and mobile user. Routing protocols for WiMAX mobile ad-hoc networks have to face the challenge of frequently changing topology, low transmission power, asymmetric links and mainly overhead problems. Ad-hoc on Demand Distance Vector (AODV) is one of the widely used routing protocols. In this paper Source Route path Accumulation Approach (SRA) is proposed for improving the performance of Ad hoc On Demand Routing Protocol (AODV) to overcome the problems of delay and overhead up to a large extent as comparison to basic AODV protocols. The protocol, AODV-SRA, incorporates source route path accumulation during the route discovery process in AODV to attain extra routing information. In this approach when the RREQ and RREP messages are generated or forwarded by the nodes in the network, each node appends its own address on these route discovery messages. Hence, at any point the RREQ packet contains a list of all the nodes traversed. Each node also updates its routing table with all the information contained in the control messages. The performance of AODV with modified AODV-SRA is compared by NS-2 simulation software under a variety of network conditions. It is also demonstrated how a small change to the AODV protocol can lead to significantly improved performance results.
Using E-Learning and ICT Courses in Educational Environment: A Review.

With the quick emergence of computers and related technology, Electronic-learning (E-learning) and Information Communication and Technology (ICT) have been extensively utilized in the education and training field. Miscellaneous methods of integrating computer technology and the context in which computers are used have affected student learning in many different ways. Integration of technology can help to create courses that are easier and more effective for learners, especially if ICT and E-learning are integrated into the educational process. ICT, when used in a sufficient and suitable manner, can help learners to understand IT better. Moreover, it can help learners to use the absolutely necessary skills which can guarantee success in empowering the learners with IT awareness and skills which are essential for success in today’s knowledge economy. This study aims to conduct a survey on the role of E-learning and ICT courses in educational environment. By having ICT courses available online via E-learning, every learner will adapt and be comfortable with the continuous upcoming technologies and innovations.
Une approche MDS hybride pour l'exploration visuelle interactive

The paper presents a novel technique for the exploration of an information space where elements are associated with a taxonomy and where each element has an associated attribute vector. A hybrid MDS method is at the core of the method. The underlying algorithm embeds elements in the 2D plane, trying to place "similar" elements close to one another. The dynamic character of the algorithm makes it a well suited tool for interactive exploration. Our first results presented here confirm our approach as a tool relevant for finding merging opportunities between companies based on various economic characteristics.
A New Approach of an Intelligent E-Learning System Based On Learners' Skill Level and Learners' Success Rate

Learners usually meet cognitive overload and disorientation problems when using e-learning system. At present, most of the studies in e-learning either concentrate on the technological aspect or focus on adapting learner's interests or browsing behaviors, while, learner's skill level and learners' success rate is usually neglected. In this paper, the authors propose an online course generation based not only on the difficulty level of a learning unit, but also the changing learning performance of the individual learner during the learning process. Therefore, considering learner's skill level and learners' success rate can promote personalized learning performance. Learners' skill level is obtained from pre-test result analysis, while learners' success rate is acquired through specific tests after completing a learning unit. After computing success rate of a learning unit, the system then modifies the difficulty level of the corresponding learning unit to update courseware material sequencing. Experiment results indicate that applying the proposed intelligent e-learning system can generate high quality learning paths, and help learners to learn more effectively.
Clinical changes in periodontal subjects with the probiotic Lactobacillus reuteri Prodentis: A preliminary randomized clinical trial

Abstract Objectives. The aim of this study was to assess the clinical effect of the administration of Lactobacillus reuteri Prodentis as a probiotic agent in the treatment of initial to moderate chronic periodontitis. Secondary objectives were to evaluate the patient ‘compliance' factor and to observe the potential side-effects of the probiotic agent. Materials and methods. Twenty systemically healthy, non-smoking subjects with initial-to-moderate chronic periodontitis were enrolled in this 1-month double-blind, placebo-controlled, randomized clinical trial. Subjects were randomly assigned to receive tablets containing Lactobacillus reuteri Prodentis or placebo once a day for 30 days. Clinical parameters were collected at baseline and 30 days post-treatment. Results. Periodontal clinical parameters were improved in the test group after a 30-day intervention. The test group demonstrated a statistically significant reduction (p < 0.05) in all the periodontal parameters included in the study (plaque index, bleeding on probing and pocket probing depths), while the control group treated with placebo did not show any statistically significant change in periodontal parameters. Conclusions. These data indicate that oral administration of Lactobacillus reuteri Prodentis improved the short-term clinical outcomes in non-smoking patients with initial-to-moderate chronic periodontitis.
Regulation of epithelial permeability by the actin cytoskeleton

The actin cytoskeleton is a dynamic structure necessary for cell and tissue organization, including the maintenance of epithelial barriers. The epithelial barrier regulates the movement of ions, macromolecules, immune cells, and pathogens, and is thus essential for normal organ function. Disruption in the epithelial barrier has been shown to coincide with alterations of the actin cytoskeleton in several disease states. These disruptions primarily manifest as increased movement through the paracellular space, which is normally regulated by tight junctions (TJ). Despite extensive research demonstrating a direct link between the actin cytoskeleton and epithelial permeability, our understanding of the physiological mechanisms that link permeability and tight junction structure are still limited. In this review, we explore the role of the actin cytoskeleton at TJ and present several areas for future study. © 2011 Wiley Periodicals, Inc
The impact of FDI and technological innovation on eastern, middle and western China’s economics

Using panel data of 30 various provinces and municipalities in China from 1994 to 2003, we analyze the effect of foreign direct investment and technological innovation on three geographical regions in China: the east, the middle and the west. With the fixed effects regression model of panel data, the results show that foreign direct investments in the eastern region mostly have positive effects, however in the middle regions and in the western regions the effect on the economy is not clear. In addition, in accordance with the eastern, the middle and the western regions grouped study. Based on the experimental results, we believe that there is a positive correlation between the FDI technology ldquospillover effectrdquo and the technology innovation.
Deep non-contact photoacoustic initial pressure imaging

Photoacoustic imaging techniques have been extensively developed for biomedical applications, including functional and molecular imaging, due in part to their high optical contrast, high spatial resolution, and non-ionizing imaging properties. However, there are currently depth limitations in cellular-resolution, optically focused photoacoustic microscopy systems. In addition, most common photoacoustic systems need to be in contact with the sample through an ultrasound medium. In this work, by taking advantage of large photoacoustic initial pressures, all-optical non-contact optical resolution photoacoustic imaging is reported at depths beyond the optical transport mean-free path of the excitation wavelength. The proposed technique is called deep photoacoustic remote sensing (dPARS) microscopy. Visible pulsed excitation wavelengths are used to produce large initial-pressure-induced refractive index modulations in absorbing targets. These localized pressure rises create transient variations to the local scattering properties, which are detected as back-reflected intensity modulations from a deep-penetrating interrogation beam and do not require an interferometric detection pathway. Experiments demonstrate that dPARS is capable of providing optical resolution images to depths of 2.5 mm in tissue-mimicking scattering media. Signal-to-noise ratio ∼50 dB is reported for in vivo imaging of microvascular networks. Also, imaging of single red blood cells, oxygen saturation mapping, and deep-vascular imaging applications are demonstrated. dPARS’s capabilities such as remote sensing, deep optical resolution imaging, and high signal-to-noise ratio, may yield new opportunities for several pre-clinical and clinical applications.
High Rate of Recanalization of Middle Cerebral Artery Occlusion During 2-MHz Transcranial Color-Coded Doppler Continuous Monitoring Without Thrombolytic Drug

Background and Purpose— Experimental evidence indicates that ultrasound can accelerate thrombolysis. We report our findings on early recanalization during transcranial color-coded Doppler (TCCD) continuous monitoring in acute stroke patients with middle cerebral artery (MCA) main stem occlusion. Methods— We performed continuous TCCD monitorings in 6 consecutive patients with acute MCA main stem occlusion using a 2-MHz transducer. Patients were not treated with recombinant tissue plasminogen activator. Results— Partial recanalization, defined as blunted waveforms, occurred during monitoring in 5 patients (83%). The mean time to beginning of recanalization was 17.2±9.6 minutes. Complete recanalization at 24 hours occurred in only 1 patient. The mean National Institutes of Health Stroke Scale score in the patients who recanalized during monitoring was 21.2±4.1 at baseline, 19.2±5 at 2 hours, and 15.6±3.4 at 24 hours (P =0.1). Conclusions— In this short series of patients with acute MCA main stem occlusion, not treated with recombinant tissue plasminogen activator, we found a high rate of early partial recanalization during continuous exposure to 2-MHz ultrasound.
Effect of including relationships in the estimation of genetic parameters of beef calves.

Variances and covariances for birth weight, gain from birth to weaning (ADG), and 205-d weight were obtained from a sire-dam model and a sire-maternal grandsire model for a herd of Angus and a herd of Hereford cattle. Estimates of direct additive genetic variance (sigma 2A), maternal additive genetic variance (sigma 2M), covariance between direct and maternal additive genetic effects (sigma AM), permanent environmental variance (sigma 2PE), and residual variance (sigma 2e) were obtained both with and without the inverse of the numerator relationship matrix (A-1) included. Estimates of heritability for direct genetic effects (h2A), maternal genetic effects (h2M), and the correlation between direct and maternal effects (rAM) for birth weight were . 37, . 18, and -. 01 in Angus and . 53, . 23, and -. 19 in Herefords, respectively, for the analyses without A-1. For the analyses with A-1, estimates of h2A, h2M, and rAM were . 42, . 22, and -. 12 for Angus and . 58, . 22, and -. 13 for Herefords, respectively. Estimates of h2A, h2M, and rAM for ADG were . 43, . 15, and -. 44 in Angus and . 52, . 38, and -. 03 in Herefords, respectively, without A-1. With A-1, estimates of h2A, h2M, and rAM were . 57, . 15, and -. 32 for Angus and . 58, . 39, and -. 05 for Herefords, respectively. Estimates of h2A, h2M, and rAM for 205-d weight were . 49, . 15, and -. 46 for Angus and . 58, . 43, and -. 06 for Herefords, respectively, without A-1. With A-1, estimates of h2A, h2M, and rAM were . 63, . 16, and -. 36 for Angus and . 66, . 43, and -. 08 for Herefords, respectively. Estimates of h2A were higher with A-1 than without A-1, but estimates of h2M were similar. Using variances and covariances obtained from analyses including A-1 generally gave higher estimates of direct breeding values than using variances and covariances obtained from analyses not including A-1. Both Pearson product-moment and Spearman rank correlations were high (.99) between estimates of breeding values from the two analyses, although some changes in rank did occur.
Piecewise linear branch prediction

Improved branch prediction accuracy is essential to sustaining instruction throughput with today's deep pipelines. We introduce piecewise linear branch prediction, an idealized branch predictor that develops a set of linear functions, one for each program path to the branch to be predicted, that separate predicted taken from predicted not taken branches. Taken together, all of these linear functions form a piecewise linear decision surface. We present a limit study of this predictor showing its potential to greatly improve predictor accuracy. We then introduce a practical implementable branch predictor based on piecewise linear branch prediction. In making our predictor practical, we show how a parameterized version of it unifies the previously distinct concepts of perceptron prediction and path-based neural prediction. Our new branch predictor has implementation costs comparable to current prominent predictors in the literature while significantly improving accuracy. For a deeply pipelined simulated microarchitecture our predictor with a 256 KB hardware budget improves the harmonic mean normalized instructions-per-cycle rate by 8% over both the original path-based neural predictor and 2Bc-gskew. The average misprediction rate is decreased by 16% over the path-based neural predictor and by 22% over 2Bc-gskew.
The recommender problem revisited

In 2006, Netflix announced a $1M prize competition to advance recommendation algorithms. The recommendation problem was simplified as the accuracy in predicting a user rating measured by the Root Mean Squared Error (RMSE). While that formulation helped get the attention of the research community in the area, it may have put an excessive focus on what is simply one of the many possible approaches to recommendations. In this tutorial we will describe different components of modern recommender systems such as: personalized ranking, similarity, explanations, context-awareness, or search as recommendation. We will use the Netflix use case as a driving example of a prototypical industrial-scale recommender system that has evolved from focusing on rating prediction to full page optimization. We will also review the usage of modern algorithmic approaches that include algorithms such as Factorization Machines [9], Restricted Boltzmann Machines [10], SimRank [7], Deep Neural Networks, or Listwise Learning-to-rank [6, 12, 11]. The original recommendation problem was formulated around the existence of explicit user ratings. However, recommender systems can be built using different kinds of data including implicit behavioral data, social connections, or demographics. In this tutorial we will review the usage of different data types and discuss what the availability of Big Data has brought into the research area. Finally, and also related to the availability of large quantities of data, we will talk about how system and architectural decisions play a role in understanding the recommender problem. This tutorial is in part based on recent publications by the author [5, 1, 8, 2, 4, 3].
MEANT 2.0: Accurate semantic MT evaluation for any output language

We describe a new version of MEANT, which participated in the metrics task of the Second Conference on Machine Translation (WMT 2017). MEANT 2.0 uses idf-weighted distributional ngram accuracy to determine the phrasal similarity of semantic role ﬁllers and yields better correlations with human judgments of translation quality than earlier versions. The improved phrasal similarity enables a subversion of MEANT to accurately evaluate translation adequacy for any output language, even languages without an automatic semantic parser. Our results show that MEANT, which is a non-ensemble and untrained metric, consistently performs as well as the top participants in previous years - including ensemble and trained ones - across different output languages. We also present the timing statistics for MEANT for better estimation of the evaluation cost. MEANT 2.0 is open source and publicly available. 1
Blurred Image Restoration Using Fast Blur-Kernel Estimation

Motion blur is usually generated when people captured a picture in the daily life. This kind of blur is often non-liner motion and may cause the blurred contents seriously in this image. Hence, how to remove the blurred image into a clear image becomes a very important scheme. In this paper, the primary aim is to propose an efficient blurred image restoration method based on fast blur-kernel estimation, which can quickly find the best kernel from a set of kernels. Many state-of-the-art methods for motion blur estimation usually use the recursive method to estimate motion blur kernel. However, it is quite time-consuming. In order to reduce the computational time, we use iterative phase retrieval algorithm and normalized sparsity measure to quickly obtain the best kernel and to achieve the deblurring. Experimental results verify that this approach can effectively speed up the executing time and obtain the best motion blur kernel and maintain the high quality of image deblurring.
Learning Pedagogical Policies from Few Training Data

Learning a pedagogical policy in an Adaptive Educational System (AIES) fits as a Reinforcement Learning (RL) problem. However, to learn pedagogical policies requires to acquire a huge amount of experience interacting with the students, so applying RL to the AIES from scratch is infeasible. In this paper we describe RLATES, an AIES that uses RL to learn an accurate pedagogical policy to teach a course of Data Base Design. To reduce the experience required to learn the pedagogical policy, we propose to use an initial value function learned with simulated students, whose model is provided by an expert as a Markov Decision Process. Empirical results demonstrate that the value function learned with the simulated students and transferred to the AIES is a very accurate initial pedagogical policy. The evaluation is based on the interaction of more than 70 Computer Science undergraduate students, and demonstrates that an efficient guide through the contents of the educational system is obtained.