Miracle-dz/UniFAR-FTUs huggingface dataset:
INAOE's Participation at PAN'15: Author Profiling task

In this paper, we describe the participation of the Language Technolo- gies Lab of INAOE at PAN 2015. According to the Author Profiling (AP) liter- ature. In this paper we take such discriminative and descriptive information into a new higher level exploiting a combination of discriminative and descriptive representations. For this we use dimensionality reduction techniques on the top of typical discriminative and descriptive textual features for AP task. The main idea is that each representation, using the full feature space, automatically highlights the different stylistic and thematic properties in the documents. Specifically, we propose the joint use of Second Order Attributes (SOA) and Latent Semantic Analysis (LSA) techniques to highlight discriminative and descriptive properties respectively. In order to evaluate our approach, we compare our proposal against a standard Bag-of-Words (BOW), SOA and LSA representations using the PAN 2015 corpus for AP. Experimental results in AP show that the combination of SOA and LSA outperforms the BOW and each individual representation, which gives evidence of its usefulness to predict gender, age and personality profiles. More importantly, according to the PAN 2015 evaluation, the proposed approach are in the top 3 positions in every dataset.
How Much Does Immigration Boost Innovation?

We measure the extent to which skilled immigrants increase innovation in the United States by exploring individual patenting behavior as well as state-level determinants of patenting. The 2003 National Survey of College Graduates shows that immigrants patent at double the native rate, and that this is entirely accounted for by their disproportionately holding degrees in science and engineering. These data imply that a one percentage point rise in the share of immigrant college graduates in the population increases patents per capita by 6%. This could be an overestimate of immigration's benefit if immigrant inventors crowd out native inventors, or an underestimate if immigrants have positive spill-overs on inventors. Using a 1940-2000 state panel, we show that immigrants do have positive spill-overs, resulting in an increase in patents per capita of 9-18% in response to a one percentage point increase in immigrant college graduates. We isolate the causal effect by instrumenting the change in the share of skilled immigrants in a state with the state's predicted increase in the share of skilled immigrants. We base the latter on the 1940 distribution across states of immigrants from various source regions and the subsequent national increase in skilled immigrants from these regions.
A Class of Algebraic Rate-Compatible Codes for Loss Recovery in Packet Networks

In this paper, a new class of algebraic rate-compatible (ARC) codes is presented and its applications to packet networks are considered. The ARC codes can be encoded incrementally using Chinese remained theory and can be decoded using Gaussian elimination. The new codes cover a wide range of code rate from frac{1}{2} to 1 and are perfect rate compatible in this range. When operated on erasure channel, the new codes approach very close to the capacity and is better than LT codes for small packet number k. Simulation is carried out to evaluate the performance and the results indicate that ARC codes are suitable for bandwidth efficient applications.
Owners and Ecological Corporate Entrepreneurship: The Effect of Family Ownership on Eco-innovation

This study examines the effect of family ownership on firm-level engagement in eco-innovation. Building on institutional theory and socioemotional wealth theory, we develop a model outlining the mediating role of concern for company reputation gains and the moderating role of the owning-family’s transgenerational intentions and of its local embeddedness. Our model is tested with data from the German part of the Community Innovation Survey using nonlinear moderated mediation analysis. We find support for most of our hypotheses and discuss key academic and practical implications.
Expression of SFRP Family Proteins in Human Keratoconus Corneas

We investigated the expression of the secreted frizzled-related proteins (SFRPs) in keratoconus (KC) and control corneas. KC buttons (∼8 mm diameter) (n = 15) and whole control corneas (n = 7) were fixed in 10% formalin or 2% paraformaldehyde and subsequently paraffin embedded and sectioned. Sections for histopathology were stained with hematoxylin and eosin, or Periodic Acid Schiff’s reagent. A series of sections was also immunolabelled with SFRP 1 to 5 antibodies, visualised using immunofluorescence, and examined with a Zeiss LSM700 scanning laser confocal microscope. Semi-quantitative grading was used to compare SFRP immunostaining in KC and control corneas. Overall, KC corneas showed increased immunostaining for SFRP1 to 5, compared to controls. Corneal epithelium in all KC corneas displayed heterogeneous moderate to strong immunoreactivity for SFRP1 to 4, particularly in the basal epithelium adjacent to cone area. SFRP3 and 5 were localised to epithelial cell membranes in KC and control corneas, with increased SFRP3 cytoplasmic expression observed in KC. Strong stromal expression of SFRP5, including extracellular matrix, was seen in both KC and control corneas. In control corneas we observed differential expression of SFRP family proteins in the limbus compared to more central cornea. Taken together, our results support a role for SFRPs in maintaining a healthy cornea and in the pathogenesis of epithelial and anterior stromal disruption observed in KC.
Assessing Migration Risk for Scientific Data Formats

The majority of information about science, culture, society, economy and the environment is born digital, yet the underlying technology is subject to rapid obsolescence. One solution to this obsolescence, format migration, is widely practiced and supported by many software packages, yet migration has well known risks. For example, newer formats – even where similar in function – do not generally support all of the features of their predecessors, and, where similar features exist, there may be significant differences of interpretation. There appears to be a conflict between the wide use of migration and its known risks. In this paper we explore a simple hypothesis – that, where migration paths exist, the majority of data files can be safely migrated leaving only a few that must be handled more carefully – in the context of several scientific data formats that are or were widely used. Our approach is to gather information about potential migration mismatches and, using custom tools, evaluate a large collection of data files for the incidence of these risks. Our results support our initial hypothesis, though with some caveats. Further, we found that writing a tool to identify “risky” format features is considerably easier than writing a migration tool.
A new strategy to reduce allelic bias in RNA-Seq readmapping

Accurate estimation of expression levels from RNA-Seq data entails precise mapping of the sequence reads to a reference genome. Because the standard reference genome contains only one allele at any given locus, reads overlapping polymorphic loci that carry a non-reference allele are at least one mismatch away from the reference and, hence, are less likely to be mapped. This bias in read mapping leads to inaccurate estimates of allele-specific expression (ASE). To address this read-mapping bias, we propose the construction of an enhanced reference genome that includes the alternative alleles at known polymorphic loci. We show that mapping to this enhanced reference reduced the read-mapping biases, leading to more reliable estimates of ASE. Experiments on simulated data show that the proposed strategy reduced the number of loci with mapping bias by ≥63% when compared with a previous approach that relies on masking the polymorphic loci and by ≥18% when compared with the standard approach that uses an unaltered reference. When we applied our strategy to actual RNA-Seq data, we found that it mapped up to 15% more reads than the previous approaches and identified many seemingly incorrect inferences made by them.
Finite-dimensional Hilbert space and frame quantization

The quantum observables used in the case of quantum systems with finite-dimensional Hilbert space are defined either algebraically in terms of an orthonormal basis and discrete Fourier transformation or by using a continuous system of coherent states. We present an alternative approach to these important quantum systems based on the finite frame quantization. Finite systems of coherent states, usually called finite tight frames, can be defined in a natural way in the case of finite quantum systems. Novel examples of such tight frames are presented. The quantum observables used in our approach are obtained by starting from certain classical observables described by functions defined on the discrete phase space corresponding to the system. They are obtained by using a finite frame and a Klauder–Berezin–Toeplitz-type quantization. Semi-classical aspects of tight frames are studied through lower symbols of basic classical observables.
Code design for joint decoding of correlated sources using algebraic network coding over AWGN channels

We consider the problem of joint decoding of signals transmitted from two correlated sources at a destination. In order to achieve high spectral efficiency at a high range of the channel signal-to-noise power (SNR), a high transmission rate is required. In this paper, we design a class of codes for joint-decoding by exploiting bit interleaved coded modulation with iterative decoding (BICM-ID) technique. Extrinsic information transfer (EXIT) chart analysis is used to evaluate the convergence property as well as to examine the optimality of the system. The simulation results show that the joint decoding with the designed code achieves the performance close to theoretical limits supported by the Slepian-Wolf and Shannon theorems.
Hunting obfuscated malware by abstract interpretation

The Problem. A malware is a program with a malicious behaviour, that is designed to replicate with no user consent and to damage software and/or data on infected machines. Malware are generally classified according to their goals an d propagation methods into viruses, worms, backdoors, Trojans, etc. A malware detector is a system that attempts to verify whether a program presents a malicious behaviour o r not. The design of efficient malware detectors is crucial for preventing serious d amages caused by malware infection. Current malware detectors (e.g. commercial vir us scanners) in general rely onstatic signature matching and, more recently, on dynamic analyses [9]. The dynamic approach executes the potentially infected program in a con trolled environment (sandbox) thus performing a run-time verification of malicious be haviours. However, smart malware may foil a dynamic analysis by modifying their behav iour when executed in a sandbox. Static signature matching classifies a program P as infected by a malware M
Learning Knowledge Bases for Text and Multimedia

Knowledge acquisition, representation, and reasoning has been one of the long-standing challenges in artificial intelligence and related application areas. Only in the past few years, massive amounts of structured and semi-structured data that directly or indirectly encode human knowledge became widely available, turning the knowledge representation problems into a computational grand challenge with feasible solutions in sight. The research and development on knowledge bases is becoming a lively fusion area among web information extraction, machine learning, databases and information retrieval, with knowledge over images and multimedia emerging as another new frontier of representation and acquisition. This tutorial aims to present a gentle overview of knowledge bases on text and multimedia, including representation, acquisition, and inference. The content of this tutorial are intended for surveying the field, as well as for educating practitioners and aspiring researchers.
Brushless DC motor control without position and speed sensors

The control strategy using a DSP-TMS320C25 is developed on the basis of the instantaneous voltage equation of the brushless DC motor. Without a position sensor, the controller has no information about rotor position: therefore, the controller determines the applied voltage according to the hypothetical rotor position, which is not necessarily coincident with the actual rotor position. Since the voltage supplied through the inverter is the actual applied voltage, it can be measured. Under the ideal condition that the hypothetical rotor position is coincident with the actual rotor position, the ideal applied voltage can be calculated by using the instantaneous voltage equation of the motor and the detected current. The difference between the actual and the ideal voltages is proportional to the angular difference of the hypothetical and actual rotor positions. Therefore, self-synchronization is possible by reducing the angular difference to zero. Once the rotor position is estimated, the motor can be operated without position and speed sensors. <<ETX>>
A Fast and Robust GJK Implementation for Collision Detection of Convex Objects

Abstract This paper presents an implementation of the Gilbert-Johnson-Keerthi algorithm for comput ing the distance between convex objects, that has improved performance, robustness, and versatility over earlier implementations. The algorithm presented here is especially suitable for use in collision detection of objects modeled using various types of geometric primitives, such as boxes, cones, and spheres, and their images under affine transformation.
Competition, Strategy, and Price Dynamics: A Theoretical and Empirical Investigation

The authors explore how competition affects dynamic pricing of new products. Dynamics of diffusion, saturation, and cost reduction due to experience are all considered, with emphasis on the last. The competition among firms is modeled as a dynamic Nash equilibrium in which each firm chooses its optimal dynamic strategy, correctly anticipating its rivals’ strategies. The dynamics of price and market share are characterized for an n-firm oligopoly. Empirical examination of price paths across eight products in the semiconductor components industry shows them to be consistent with analytical results.
A Series of Beta-Carboline Derivatives Inhibit the Kinase Activity of PLKs

Polo-like kinases play an essential role in the ordered execution of mitotic events and 4 mammalian PLK family members have been identified. Accumulating evidence indicates that PLK1 is an attractive target for anticancer drugs. In this paper, a series of beta-carboline derivatives were synthesized and three compounds, DH281, DH285 and DH287, were identified as potent new PLK inhibitors. We employed various biochemical and cellular approaches to determine the effects of these compounds on the activity of PLK1 and other mitotic kinases and on cell cycle progression. We found that these three compounds could selectively inhibit the kinase activity of purified PLK1, PLK2 and PLK3 in vitro. They show strong antitumor activity against a number of cancer cell lines with relatively low micromolar IC50s, but are relatively less toxic to non-cancer cells (MRC5). Moreover, these compounds could induce obvious accumulation of HeLa cells in G2/M and S phases and trigger apoptosis. Although MRC5 cells show clear S-phase arrest after treatment with these compounds, the G2/M arrest and apoptosis are less insignificant, indicating the distinct sensitivity between normal and cancer cells. We also found that HeLa cells treated with these drugs exhibit monopolar spindles and increased Wee1 protein levels, the characteristics of cells treated with PLK1 inhibitors. Together, these results demonstrate that DH281, DH285 and DH287 beta-carboline compounds are new PLK inhibitors with potential for cancer treatment.
Holography, UV/IR Relation, Causal Entropy Bound, and Dark Energy

The constraint on the total energy in a given spatial region is given from holography by the mass of a black hole that just fits in that region, which leads to an UV/IR relation: the maximal energy density in that region is propotional to M(p)(2)/L(2), wher M(p) is the Planck mass and L is the spatial scale of that region under consideration. Assuming that maximal black hole in the universe is formed through gravitational collapse of perturbations in the universe, then the "Jeans" scale of the perturbations gives a causal connection scale R(CC). For gravitational perturbations, R(CC)(-2) = Max ((H) over dot + 2H(2), -(H) over dot) for a flat universe. We study the cosmological dynamics of the corresponding vacuum energy density by choosing the causal connection scale as the IR cutoff in the UV/IR relation, in the cases of the vacuum energy density as an independently conserved energy component and an effective dynamical cosmological constant, respectively. It turns out that only the case with the choice R(CC)(-2) = (H) over dot + 2H(2), could be consistent with the current cosmological observations when the vacuum density appears as an independently conserved energy component. In this case, the model is called holographic Ricci scalar dark energy model in the literature.
Nonnegative unmixing methodology applied on Brillouin Optical Fiber Sensor

As a complement to conventional sensors, Distributed Optical Fiber Sensors (DOFS) have gradually played a prominent role in Structural Health Monitoring (SHM) for the last decade. The distributed Brillouin sensor enables to measure strain along kilometers of cable with a spatial resolution of 1 meter. The challenge is to have a centimeter spatial resolution to improve structure defaults detection and localization. A numerical model, based on the sensor physic, is first proposed in order to study Brillouin spectra distortion depending on strain distribution within spatial resolution. Then, based on nonnegative least squares (NNLS) problem, Brillouin spectra are decomposed into several elementary spectra. The estimated central frequencies and maxima permit to estimate a centimeter frequency distribution within the spatial resolution. It has been verified with numerical and experimental data: that method enables to enhance the accuracy and spatial resolution of the sensor from meter to centimeter.
Mary, Mary, Quite Contrary: Exposing Twitter Users to Contrarian News

Polarized topics often spark discussion and debate on social media. Recent studies have shown that polarized debates have a specific clustered structure in the endorsement net- work, which indicates that users direct their endorsements mostly to ideas they already agree with. Understanding these polarized discussions and exposing social media users to con- tent that broadens their views is of paramount importance. The contribution of this demonstration is two-fold. (i) A tool to visualize retweet networks about controversial issues on Twitter. By using our visualization, users can understand how polarized discussions are shaped on Twitter, and explore the positions of the various actors. (ii) A solution to reduce polarization of such discussions. We do so by exposing users to information which presents a contrarian point of view. Users can visually inspect our recommendations and understand why and how these would play out in terms of the retweet network. Our demo (https://users.ics.aalto.fi/kiran/reducingControversy/ homepage) provides one of the first steps in developing automated tools that help users explore, and possibly escape, their echo chambers. The ideas in the demo can also help content providers design tools to broaden their reach to people with different political and ideological backgrounds.
Oceanic Protists

extraordinary species diversity and variety of interactions of protists in the sea are only now being fully appreciated. Figure 1 shows representative examples of marine protists, and of methods used to visualize these microbes. Protists can be autotrophic or heterotrophic. The former, also called microscopic algae, contain chloroplasts, thrive by photosynthesis, and are at the base of all oceanic food webs, with the exception of deep-sea chemosynthetic ecosystems. There is a general trend for > 20-μm sized phytoplankton (microplankton), such as diatoms and dinoflagellates, to dominate episodically in coastal waters, while in the open ocean 2–20-μm sized cells (nanoplankton), such as coccolithophorids, sporadically form massive blooms that can be seen from space. However, during nonbloom seasons, even smaller cells (picoplankton—prokaryotes and eukaryotes less than a few micrometers in size) typically dominate phytoplankton biomass and production (Li, 2002; Worden et al.,
Terrain Modelling from Feature Primitives

We introduce a compact hierarchical procedural model that combines feature‐based primitives to describe complex terrains with varying level of detail. Our model is inspired by skeletal implicit surfaces and defines the terrain elevation function by using a construction tree. Leaves represent terrain features and they are generic parametrized skeletal primitives, such as mountains, ridges, valleys, rivers, lakes or roads. Inner nodes combine the leaves and subtrees by carving, blending or warping operators. The elevation of the terrain at a given point is evaluated by traversing the tree and by combining the contributions of the primitives. The definition of the tree leaves and operators guarantees that the resulting elevation function is Lipschitz, which speeds up the sphere tracing used to render the terrain. Our model is compact and allows for the creation of large terrains with a high level o detail using a reduced set of primitives. We show the creation of different kinds of landscapes and demonstrate that our model allows to efficiently control the shape and distribution of landform features.
Characterizing Satellite-Based Communications to provide Seamless and Effective Transoceanic Data Dissemination

Weather communications and associated data products are singularly important to the operation and control of commercial aircraft especially those flying in the transoceanic region where unpredictable weather patterns and turbulence can occur with little advanced warning. The transoceanic element of the WINCOMM Project is researching methods to improve the dissemination of weather products to the cockpit by utilizing commercial satellites and transitioning to packet-based solutions. For on-demand weather products, packet-based services will provide an efficient mechanism for transferring data than the current circuit switched implementation. This paper discusses the progress achieved in the transoceanic research area. First, the testbed architecture used for testing concepts will be presented; it provides a live connection to the Inmarsat Satellite Constellation. Secondly, the Quality of Service (QoS) algorithms, as implemented in Linux, will be discussed and the configurations of applicable algorithms to this scenario will be shown. In addition, future plans will be presented that transitions the research work from the existing Inmarsat infrastructure to the new I4 satellites.