Miracle-dz/UniFAR-FTUs huggingface dataset:
DeepCalib: a deep learning approach for automatic intrinsic calibration of wide field-of-view cameras

Calibration of wide field-of-view cameras is a fundamental step for numerous visual media production applications, such as 3D reconstruction, image undistortion, augmented reality and camera motion estimation. However, existing calibration methods require multiple images of a calibration pattern (typically a checkerboard), assume the presence of lines, require manual interaction and/or need an image sequence. In contrast, we present a novel fully automatic deep learning-based approach that overcomes all these limitations and works with a single image of general scenes. Our approach builds upon the recent developments in deep Convolutional Neural Networks (CNN): our network automatically estimates the intrinsic parameters of the camera (focal length and distortion parameter) from a single input image. In order to train the CNN, we leverage the great amount of omnidirectional images available on the Internet to automatically generate a large-scale dataset composed of millions of wide field-of-view images with ground truth intrinsic parameters. Experiments successfully demonstrated the quality of our results, both quantitatively and qualitatively.
What do researchers think about altmetrics and are they familiar with their abilities

The rise of the Web 2.0 (Social web) has given the main incentive to the creation of altmetrics, which are social web metrics for academic purposes. They can, theoretically, be used in an evaluative role and as an information seeking aid, both tasks reserved until recently for traditional bibliometrics. If altmetrics are to be trusted then the claims about both of these tasks must be acceptable and verifiable. Regarding the growing number of scientific publications on altmetrics and its methods, researchers in the field of scientific metrics are now trying to assess this possibility as well. The question is which parts of these new metrics are acceptable for a scientific community? Decades were needed to establish a reasonable confidence in classical bibliometrical methods, such as citation analysis, so how long will it take for altmetrics to gain the same level of trust? This is an important although quite neglected topic. The paper presents a continuation of a survey on information behaviour of Slovenian researchers in 2011 on a random sample obtained from the complete list of researchers in Slovenia. The results confirm the already detected low level of use and acceptance of Web 2.0 tools among Slovenian researchers. On the other hand, the results also show a strong interest in altmetrics and the possibilities for alternative evaluation. This interest calls for further research into the possibilities offered by these new metrics. We need to explore the applicability, use and acceptance of altmetrics and its various possible sources and indicators in the scientific community. Also, we need to inform the scientists about these new possibilities. This should be an important task for all who are involved professionally (research or otherwise) in the field of scientific research evaluation. Keywords : altmetrics, social web, bibliometrics, evaluation, scientific research
Inverse elastic shell design with contact and friction

We propose an inverse strategy for modeling thin elastic shells physically, just from the observation of their geometry. Our algorithm takes as input an arbitrary target mesh, and interprets this configuration automatically as a stable equilibrium of a shell simulator under gravity and frictional contact constraints with a given external object. Unknowns are the natural shape of the shell (i.e., its shape without external forces) and the frictional contact forces at play, while the material properties (mass density, stiffness, friction coefficients) can be freely chosen by the user. Such an inverse problem formulates as an ill-posed nonlinear system subject to conical constraints. To select and compute a plausible solution, our inverse solver proceeds in two steps. In a first step, contacts are reduced to frictionless bilateral constraints and a natural shape is retrieved using the adjoint method. The second step uses this result as an initial guess and adjusts each bilateral force so that it projects onto the admissible Coulomb friction cone, while preserving global equilibrium. To better guide minimization towards the target, these two steps are applied iteratively using a degressive regularization of the shell energy. We validate our approach on simulated examples with reference material parameters, and show that our method still converges well for material parameters lying within a reasonable range around the reference, and even in the case of arbitrary meshes that are not issued from a simulation. We finally demonstrate practical inversion results on complex shell geometries freely modeled by an artist or automatically captured from real objects, such as posed garments or soft accessories.
Connectionist Taxonomy Learning

The paper at hand describes an approach to automatise the creation of a class taxonomy. Information about objects, e.g. "a tank is armored and moves by track", but no prior knowledge about taxonomy structure is presented to a connectionist system which organizes itself by means of activation spreading (McClelland and Rumelhart, 1981) and weight adjustments. The resulting connectionist network has a form of a taxonomy sought-after.
Computers and Writing: Models and Tools

This collection reports on research and development in the field of computers and writing, including the design of computational models and tools to teach writing. The book reviews computational, cognitive and educational factors, written by researchers at the forefront of this area as well as practicing teachers already using writing software in the classroom. The volume focuses on the value of computers for writers, the use of computers to gain or develop writing skills, or the effect of computers on human writing processes. The chapters specifically address the following issues: how is writing software evaluated; will a machine complement, replace or interfere with a writing teacher; how are software writing tools developed; how are software writing tools accurately used; what new writing processes will people use when they use machines; can writing be modeled well enough to create worthwhile computer writing tools; where will these models come from; and can computer-generated text be of value in the classroom.
Parallel iterative solvers for real-time elastic deformations

Physics-based animation of elastic materials allows to simulate dynamic deformable objects such as fabrics, human tissue, hair, etc. Due to their complex inner mechanical behaviour, it is difficult to replicate their motions interactively and accurately at the same time. This course introduces students and practitioners to several parallel iterative techniques to tackle this problem and achieve elastic deformations in real-time. We focus on techniques for applications such as video games and interactive design, with fixed and small hard time budgets available for physically-based animation, and where responsiveness and stability are often more important than accuracy, as long as the results are believable. The course focuses on solvers able to fully exploit the computational capabilities of modern GPU architectures, effectively solving systems of hundreds of thousands of nonlinear equations in a matter of few milliseconds. The course introduces the basic concepts concerning physics-based elastic objects, and provide an overview of the different types of numerical solvers available in the literature. Then, we show how some variants of traditional solvers can address real-time animation and assess them in terms of accuracy, robustness and performance. Practical examples are provided throughout the course, in particular how to apply the depicted solvers to Projective Dynamics and Position-based Dynamics, two recent and popular physics models for elastic materials.
Investigation on the cutaneous/proprioceptive contribution to the force sensation induced by electrical stimulation above tendon

A method to present force sensation based on electrical stimulation to the tendon has been suggested, and the occurrence of the sensation was considered due to the contribution of proprioceptors such as Golgi tendon organs. However, there was no clear evidence about the contributing receptors and because the method uses percutaneous electrical stimulation, there are other candidates, the cutaneous receptors. In this paper, we conducted experiments to determine whether the force sensation generated by this method is due to cutaneous sensation or proprioception, by changing the effective depth of electrical stimulation with electrodes spacing. As a result, it was shown that when the electrical stimulation could reach to deep tissue receptors, the force sensation was felt clearer, suggesting possible contribution of the proprioceptor.
Unifying the stochastic and the adversarial Bandits with Knapsack

This work investigates the adversarial Bandits with Knapsack (BwK) learning problem, where a player repeatedly chooses to perform an action, pays the corresponding cost of the action, and receives a reward associated with the action. The player is constrained by the maximum budget that can be spent to perform the actions, and the rewards and the costs of these actions are assigned by an adversary. This setting is studied in terms of expected regret, defined as the difference between the total expected rewards per unit cost corresponding the best fixed action and the total expected rewards per unit cost of the learning algorithm. We propose a novel algorithm EXP3.BwK and show that the expected regret of the algorithm is order optimal in the budget. We then propose another algorithm EXP3++. BwK, which is order optimal in the adversarial BwK setting, and incurs an almost optimal expected regret in the stochastic BwK setting where the rewards and the costs are drawn from unknown underlying distributions. These results are then extended to a more general online learning setting, by designing another algorithm EXP3++. LwK and providing its performance guarantees. Finally, we investigate the scenario where the costs of the actions are large and comparable to the budget. We show that for the adversarial setting, the achievable regret bounds scale at least linearly with the maximum cost for any learning algorithm, and are significantly worse in comparison to the case of having costs bounded by a constant, which is a common assumption in the BwK literature.
High frequency deadbeat control of three phase PWM inverter used for uninterruptible power supply

A digital control technique is proposed to obtain a sinusoidal three-phase pulsewidth-modulated (PWM) inverter output. By sensing two line-to-line voltages, the required pulse patterns for deadbeat response can be computed in real time using the predicted voltages at 9 kHz sampling frequency. This closed-loop voltage control inherently results in a very low total harmonic distortion and a very rapid transient response with less filter capacity. The modeling technique, theoretical analysis, simulations, and experimental results are described. <<ETX>>
Chromosome Doubling-Enhanced Biomass and Dihydrotanshinone I Production in Salvia miltiorrhiza, A Traditional Chinese Medicinal Plant

The root of Chinese sage (Salvia miltiorrhiza Bunge) was regarded as top-grade Chinese medicine two thousand years ago, according to Shen Nong Materia Medica. The aim of this study is to develop an easy and reliable means for obtaining tetraploids (4x plants) via thidiazuron-induced direct organogenesis in the presence of colchicine. The resulting 4x plants showed significantly enhanced agronomic traits, including the size of stomata, leaflet, pollen, and seed as well as shoot length, root diameter, number of leaves, and fresh weight of plant. In addition, an obvious reduction of length to width ratio was found in the 4x plants, including stomata, leaflets, pollens, seeds, and roots. The 4x ploidy state of the plants was stable as was proved by evaluation of selection indicators as well as consistent ploidy level at 10th generation plantlets and also on 4x seedlings obtained via self-pollination. The major bioactive compounds, salvianolic acid B, tanshinone I, tanshinone IIA, dihydrotanshinone I and cryptotanshinone, as well as total tanshinones were determined by high performance liquid chromatography (HPLC). The concentrations of dihydrotanshinone I and total tanshinones in the root extract of the 4x plants were significantly higher when compared with the 2x plants. This present study developed a simple and efficient system for inducing and subculture of tetrapolids which have stable ploidy level, enhanced growth characteristics as well as the content of dihydrotanshinone I in the root of S. miltiorrhiza.
Public/private interactive wearable projection display

We propose a wearable projection system that displays both public and private information concurrently. The system is composed of a 2-layer forearm mounted screen and a head worn device which projects images on the screen. The screen can be switched between two modes, light-diffusing mode, where projected image is visible to the surrounding viewers and light-transmitting mode, where projected image is only limited to the user. We conducted a set of design workshop to identify the optimal placement and interactions with this display system. We also implemented three display methods to present public or private information, which are contextualized with several use-case applications, supported with four sets of gestures.
Robust flow-guided neural prediction for sketch-based freeform surface modeling

Sketching provides an intuitive user interface for communicating free form shapes. While human observers can easily envision the shapes they intend to communicate, replicating this process algorithmically requires resolving numerous ambiguities. Existing sketch-based modeling methods resolve these ambiguities by either relying on expensive user annotations or by restricting the modeled shapes to specific narrow categories. We present an approach for modeling generic freeform 3D surfaces from sparse, expressive 2D sketches that overcomes both limitations by incorporating convolution neural networks (CNN) into the sketch processing workflow. Given a 2D sketch of a 3D surface, we use CNNs to infer the depth and normal maps representing the surface. To combat ambiguity we introduce an intermediate CNN layer that models the dense curvature direction, or flow, field of the surface, and produce an additional output confidence map along with depth and normal. The flow field guides our subsequent surface reconstruction for improved regularity; the confidence map trained unsupervised measures ambiguity and provides a robust estimator for data fitting. To reduce ambiguities in input sketches users can refine their input by providing optional depth values at sparse points and curvature hints for strokes. Our CNN is trained on a large dataset generated by rendering sketches of various 3D shapes using non-photo-realistic line rendering (NPR) method that mimics human sketching of free-form shapes. We use the CNN model to process both single- and multi-view sketches. Using our multi-view framework users progressively complete the shape by sketching in different views, generating complete closed shapes. For each new view, the modeling is assisted by partial sketches and depth cues provided by surfaces generated in earlier views. The partial surfaces are fused into a complete shape using predicted confidence levels as weights. We validate our approach, compare it with previous methods and alternative structures, and evaluate its performance with various modeling tasks. The results demonstrate our method is a new approach for efficiently modeling freeform shapes with succinct but expressive 2D sketches.
The hematological diagnosis of the Systemic Inflammatory Response Syndrome in horses

We have sampled 102 adult horses, of both sexes. The horses were placed into twocategories, SIRS (37 horses) and non-SIRS, based on their fibrinogen, blood MPXI and serum ironvalues. The blood work of the SIRS-diagnosed horses was then evaluated to highlight possibleconnections to the diagnosis, especially in terms of the leukopenia/leukocytosis that are consideredmarkers of SIRS in human medicine.Only half of these horses showed symptoms of leukocytosis/leukopenia in addition to highfibrinogen and low serum iron and MPXI, therefore showing that the algorithm used in humanmedicine cannot be applied to horses in its whole.
JUINET-a novel low cost universal networking technique

Traditionally, the RS232 serial interface standard is used for point-to-point interconnection, and supported by almost every intelligent device for industrial automation. For modern applications, distributed systems are becoming popular. This paper describes a novel low cost add-on circuit that can be externally attached to standard RS232 ports to implement a fieldbus like peer-to-peer network with programmable baud rates up to 115 K baud. JUINET-a multi-master network with CSMA/CD has been implemented to reuse existing devices in a variety of distributed applications in simulation and process automation.
Patterns of brown bear damages on apiaries and management recommendations in the Cantabrian Mountains, Spain

Large carnivores are often persecuted due to conflict with human activities, making their conservation in human-modified landscapes very challenging. Conflict-related scenarios are increasing worldwide, due to the expansion of human activities or to the recovery of carnivore populations. In general, brown bears Ursus arctos avoid humans and their settlements, but they may use some areas close to people or human infrastructures. Bear damages in human-modified landscapes may be related to the availability of food resources of human origin, such as beehives. However, the association of damage events with factors that may predispose bears to cause damages has rarely been investigated. We investigated bear damages to apiaries in the Cantabrian Mountains (Spain), an area with relatively high density of bears. We included spatial, temporal and environmental factors and damage prevention measures in our analyses, as factors that may influence the occurrence and intensity of damages. In 2006–2008, we located 61 apiaries, which included 435 beehives damaged in the study area (346 km2). The probability of an apiary being attacked was positively related to both the intensity of the damage suffered the year before and the distance to the nearest damaged apiary, and negatively related to the number of prevention measures employed as well as the intensity of the damage suffered by the nearest damage apiary. The intensity of damage to apiaries was positively related to the size of the apiary and to vegetation cover in the surroundings, and negatively related to the number of human settlements. Minimizing the occurrence of bear damages to apiaries seems feasible by applying and maintaining proper prevention measures, especially before an attack occurs and selecting appropriate locations for beehives (e.g. away from forest areas). This applies to areas currently occupied by bears, and to neighbouring areas where dispersing individuals may expand their range.
Near optimum decoding of product codes

A new iterative decoding algorithm for product codes (block) based on soft decoding and soft decision output of the component codes is described in the paper. Monte Carlo simulations of the bit error rate (BER) after decoding using this new algorithm for different product codes indicate coding gains of up to 8 dB. This new coding scheme is attractive for digital transmission systems requiring powerful coding schemes with a high code rate (R>0.8). In the paper the authors compare their coding scheme with one of the best coding schemes, the "turbo-codes", in terms of BER performance.
CSCL and Learning Analytics: Opportunities to Support Social Interaction, Self-Regulation and Socially Shared Regulation

Research has generated deep insights into computer-supported collaborative learning (CSCL), but the cycle of impact on practice is relatively lengthy and slow. In contrast, work in learning analytics attempts to leverage the collection and analysis of data to improve learning processes and outcomes in-situ. Developing learning analytics to support CSCL thus offers the opportunity to make our research actionable in an immediate way by using data collected on collaborative processes in-progress to inform their future trajectories. Efforts in this direction are specifically promising in support of students’ selfand socially sharedregulation of their learning. Data on collaborative and metacognitive activities can inform collaborating groups and help them to improve future joint efforts. In this symposium we bring together a collection of five papers that are exploring the space of connection between CSCL, learning analytics and self-regulation to advance thinking around these issues.
A novel SLC40A1 p.Y333H mutation with gain of function of ferroportin: A recurrent cause of haemochromatosis in China

Haemochromatosis type 4, also known as ferroportin disease, is an autosomal dominant genetic disorder caused by pathogenic mutations in the SLC40A1 gene, which encodes ferroportin 1 (FPN1). We have identified a novel SLC40A1 p.Y333H mutation in our previous study. In the present study, we tried to investigate the frequency and pathogenicity of the SLC40A1 p.Y333H mutation in haemochromatosis in China.
Hypoxia evokes increased PDI and PDIA6 expression in the infarcted myocardium of ex-germ-free and conventionally raised mice

ABSTRACT The prototypic protein disulfide isomerase (PDI), encoded by the P4HB gene, has been described as a survival factor in ischemic cardiomyopathy. However, the role of protein disulfide isomerase associated 6 (PDIA6) under hypoxic conditions in the myocardium remains enigmatic, and it is unknown whether the gut microbiota influences the expression of PDI and PDIA6 under conditions of acute myocardial infarction. Here, we revealed that, in addition to the prototypic PDI, the PDI family member PDIA6, a regulator of the unfolded protein response, is upregulated in the mouse cardiomyocyte cell line HL-1 when cultured under hypoxia. In vivo, in the left anterior descending artery (LAD) ligation mouse model of acute myocardial infarction, similar to PDI, PDIA6 protein expression was enhanced in the infarcted area (LAD+) relative to uninfarcted sham tissue or the neighbouring area at risk (LAD–) of C57BL/6J mice. Interestingly, we found that ex-germ-free (ex-GF) mice subjected to the LAD ligation model for 24 h had a reduced ejection fraction compared with their conventionally raised (CONV-R) SPF controls. Furthermore, the LAD+ area in the infarcted heart of ex-GF mice showed reduced PDIA6 expression relative to CONV-R controls, suggesting that the presence of a gut microbiota enhanced LAD ligation-triggered PDIA6 expression. Collectively, our results demonstrate that PDIA6 is upregulated in cardiomyocytes as a consequence of hypoxia. In the LAD mouse model, PDIA6 was also increased in the infarcted area under in vivo conditions, but this increase was suppressed in ex-GF mice relative to CONV-R controls. This article has an associated First Person interview with the first author of the paper. Summary: We identified PDIA6 as a hypoxia-induced element of the unfolded protein response in cardiomyocytes and infarcted mouse hearts. PDIA6 expression and ejection fractions were reduced in infarcted ex-germ-free mouse hearts.