Miracle-dz/UniFAR-FTUs huggingface dataset:
Opinion mining in Hungarian based on textual and graphical clues

Opinion Mining aims at recognizing and categorizing or extracting opinions found in unstructured text resources and is one of the most dynamically evolving subdiscipline of Computational Linguistics showing some resemblance to document classification and information extraction tasks. In this paper we propose a novel approach in Opinion Mining which combines Machine Learning models based on traditional textual and graphical clues as well. By examining subjective messages in a given forum topic dealing with a specific voting question, our system makes a prediction about the opinion of unknown people, which can be utilized to predict the forthcoming result of a referendum. The novelty of the work is that beside the regular textual clues (i.e. uni-bigrams), decisions are enhanced by using knowledge derived from a so-called response graph, which represents the interactions between the forum members. Our experimental results showed that with the help of such a graph we were able to achieve better results and significantly outperform the baseline accuracy. The promising results have reinforced our expectations that such an application can be easily adapted to any future Opinion Mining task in the election domain.
Notice of RetractionEmpirical Study on the Relationship between Salaries of Corporate Top Managers

The paper made analysis of listed companies from2004 to 2006 which were divided into two sub-samplesrespectively as state-owned listed companies and private listed companies. Results are obtained as follows: differences existed between state-owned listed companies and private listed companies in terms of the mechanism of salaries; top managerspsila salaries were in steady weak positive correlation to firm performance and firm scale but not steadily correlated to the proportion of state-owned shares; within private listed companies, top managerspsila salaries were not steadily correlatedto firm performance, firm scale or the proportion of stateowned shares; salaries of top managers in both state-owned enterprises and private enterprises were under apparent influence of regional and industrial difference.
Database architecture for content-based image retrieval

This paper describes visual interaction mechanisms for image database systems. The typical mechanisms for visual interactions are query by visual example and query by subjective descriptions. The former includes a sketch retrieval function and a similarity retrieval function, while the latter includes a sense retrieval function. We adopt both an image model and a user model to interpret and operate the contents of image data from the user''s viewpoint. The image model describes the graphical features of image data, while the user model reflects the visual perception processes of the user. These models, automatically created by image analysis and statistical learning, are referred to as abstract indexes stored in relational tables. These algorithms are developed on our experimental database system, the TRADEMARK and the ART MUSEUM.
How Each Movement Changes the Next: An Experimental and Theoretical Study of Fast Adaptive Priors in Reaching

Most voluntary actions rely on neural circuits that map sensory cues onto appropriate motor responses. One might expect that for everyday movements, like reaching, this mapping would remain stable over time, at least in the absence of error feedback. Here we describe a simple and novel psychophysical phenomenon in which recent experience shapes the statistical properties of reaching, independent of any movement errors. Specifically, when recent movements are made to targets near a particular location subsequent movements to that location become less variable, but at the cost of increased bias for reaches to other targets. This process exhibits the variance–bias tradeoff that is a hallmark of Bayesian estimation. We provide evidence that this process reflects a fast, trial-by-trial learning of the prior distribution of targets. We also show that these results may reflect an emergent property of associative learning in neural circuits. We demonstrate that adding Hebbian (associative) learning to a model network for reach planning leads to a continuous modification of network connections that biases network dynamics toward activity patterns associated with recent inputs. This learning process quantitatively captures the key results of our experimental data in human subjects, including the effect that recent experience has on the variance-bias tradeoff. This network also provides a good approximation of a normative Bayesian estimator. These observations illustrate how associative learning can incorporate recent experience into ongoing computations in a statistically principled way.
Command governors for constrained nonlinear systems: direct nonlinear vs. linearization‐based strategies

Two command governors (CG) are described for solving set-point tracking problems for nonlinear systems when pointwise-in-time input and/or state related inequality constraints have to be fulllled. A CG is a nonlinear device which is added to a primal compensated system. The CG action, based on the current state, set-point and prescribed constraints, is nalized to select, at any time, a command sequence under which the constraints are possibly fulllled with acceptable tracking performance. The two CG's, both based on the receding horizon control philosophy, diier in that one directly exploits the nonlinear model of the primal system, whereas the other is based on the property that, under some conditions, all trajectories of a nonlinear system are embedded within the trajectories of a linear time-varying (LTV) uncertain system. An example is presented so as to exhibit the relative merits of the methods.
INTERNET GAMING ADDICTION . REASONS , DIAGNOSIS , PREVENTION AND TREATMENT

We define electronic games addiction as the excessive and morbid use of electronic games (especially those taking advantage of social net working to become accessible to many users). In cases of addiction, this excessive use tends to interfere with everyday reality and to significantly influence it. Researches on the excessive use of internet structures and the problems it causes appeared as early as the 1989 (Shatton, 1989). The rapid development of the computer science and the improvement of the computer-user inter action can fully justify both the massiveness of the problem as well as the plethora of researches on the issue. Roles Video games with an international (thanks to modern technology) appeal tend to be consid ered as the most addictive ones. This games cat egory includes the creation of a virtual world in which each user is represented through a charac ter that acts on a personal or group basis. Such online games are of extreme popularity. According to the latest (2012) report by an entertainment software company, a 72% of American households with an internet connection have at least a mem ber participating in online gaming. Such high rates tend to raise concerns given the fact that online games are scientifically proven to cause among others: psychomotor disorders, desensitization of emotions, addictive coercive behavior, personality changes, depersonalization of the user, learning difficulties, and anti-social behavior. The current study by the Neuropsychology Lab of the University of Thessaly attempts at studying a group of online gaming addicts as well as at find ing ways to detect and treat the addiction. Our pre sentation’s further aim is the collection of data and the creation of rehabilitation programs in the long run.
Building a Recognition System of Speech Emotion and Emotional States

To make a decision in companies or public organizations, the priority ordering plays an essential. For example, their discussion is essential for stakeholder to achieve mutual consensus,. In the discussion, the difference among consensus building processes can affect the last conclusion. Therefore, it is necessary for analysis to find critical remarks reaching the consensus ('hfocus remark'h). However, it is a basis to confirm the gfocus remark'h that the consensus building process can understand exactly from the disagreement state consent and detailed exposition parties. The consensus discussion is very helpful to promote interaction by the speech. The paper addresses the design of recognition system and results are achieved by means of MFCC (Mel Frequency Campestral Coefficients) and HMM (Hidden Markov Model). Results in recognition of six emotion patterns obtained 86.8% recognition rate. According to the relation of emotional states and emotions we analyzed the support more objectively.
Data Language Specification via Terminal Attribution

Unstructured data have to be parsed in order to become usable. The complexity of grammar notations and the difficulty of grammar debugging limit the use of parsers for data preprocessing. We introduce a notation in which grammars are defined by simply dividing terminals into predefined classes and then splitting elements of some classes into multiple layered sub-groups. These LL(1) grammars are designed for data languages. They simplify the task of developing data parsers.
The Hemopexin Domain of Matrix Metalloproteinase-9 Activates Cell Signaling and Promotes Migration of Schwann Cells by Binding to Low-Density Lipoprotein Receptor-Related Protein

Low-density lipoprotein receptor-related protein (LRP-1) is an endocytic receptor for diverse proteins, including matrix metalloproteinase-9 (MMP-9), and a cell-signaling receptor. In the peripheral nervous system (PNS), LRP-1 is robustly expressed by Schwann cells only after injury. Herein, we demonstrate that MMP-9 activates extracellular-signal-regulated kinase (ERK1/2) and Akt in Schwann cells in culture. MMP-9 also promotes Schwann cell migration. These activities require LRP-1. MMP-9-induced cell signaling and migration were blocked by inhibiting MMP-9-binding to LRP-1 with receptor-associated protein (RAP) or by LRP-1 gene silencing. The effects of MMP-9 on Schwann cell migration also were inhibited by blocking the cell-signaling response. An antibody targeting the hemopexin domain of MMP-9, which mediates the interaction with LRP-1, blocked MMP-9-induced cell signaling and migration. Furthermore, a novel glutathione-S-transferase fusion protein (MMP-9-PEX), which includes only the hemopexin domain of MMP-9, replicated the activities of intact MMP-9, activating Schwann cell signaling and migration by an LRP-1-dependent pathway. Constitutively active MEK1 promoted Schwann cell migration; in these cells, MMP-9-PEX had no further effect, indicating that ERK1/2 activation is sufficient to explain the effects of MMP-9-PEX on Schwann cell migration. Injection of MMP-9-PEX into sciatic nerves, 24 h after crush injury, robustly increased phosphorylation of ERK1/2 and Akt. This response was inhibited by RAP. MMP-9-PEX failed to activate cell signaling in uninjured nerves, consistent with the observation that Schwann cells express LRP-1 at significant levels only after nerve injury. These results establish LRP-1 as a cell-signaling receptor for MMP-9, which may be significant in regulating Schwann cell migration and physiology in PNS injury.
Chaos control in a neural network with threshold activated coupling

The chaotic neural network is studied under the threshold activated coupling, which provides a controlled output patterns. In general the chaotic neural network constructed with chaotic neurons exhibits very rich dynamic behaviors with a nonperiodic associative memory. In the chaotic neural network, it is difficult to distinguish the stored patterns from others, because of the chaotic states of output of the network. In order to apply the nonperiodic associative memory into information search and pattern recognition, etc, it is necessary to control chaos in this chaotic neural network. Chaos in the chaotic neural network is controlled with threshold activated coupling method and the network converges on one of its stored patterns or their reverses which has the smallest Hamming distance with the initial state of the network or provides a controlled neural network with spatio-temporal patterns depending upon the nature of control.
A Visible Light Positioning system using Frequency Division Multiple Access with square waves

In this paper, a Visible Light Positioning (VLP) system using Frequency Division Multiple Access (FDMA) with square waves is presented. For the multiple access technology, the properties of square waves in the frequency domain is exploited. Neighboring LEDs will use multiples of the ground frequency of the first LED where the receiver performs a Fast Fourier Transform (FFT) and retrieves the Received Signal Strength (RSS) for every LED. In order to facilitate implementation, the LEDs are transmitting pilot tones in a non-synchronized way to the receiver, and thus requiring no backbone network. The positioning algorithm uses the RSS to perform triangulation and finds the position by taking the least square fit. Practical results show that this VLP system has position errors smaller then 10 cm when an photodiode is used which has a Field Of View (FOV) of 70°. Simulation results show that when a photodiode with a FOV of 90° is applied, the position error can drop to a few centimeter within the entire test bench surface. The key advantage of the system is the use of unsynchronized low bandwidth transmitters, leading to an easy implementation using current high efficiency LED drivers.
Evaluation of LiF:Mg,Ti (TLD-100) for Intraoperative Electron Radiation Therapy Quality Assurance

Background Purpose of the present work was to investigate thermoluminescent dosimeters (TLDs) response to intraoperative electron radiation therapy (IOERT) beams. In an IOERT treatment, a large single radiation dose is delivered with a high dose-per-pulse electron beam (2–12 cGy/pulse) during surgery. To verify and to record the delivered dose, in vivo dosimetry is a mandatory procedure for quality assurance. The TLDs feature many advantages such as a small detector size and close tissue equivalence that make them attractive for IOERT as in vivo dosimeters. Methods LiF:Mg,Ti dosimeters (TLD-100) were irradiated with different IOERT electron beam energies (5, 7 and 9 MeV) and with a 6 MV conventional photon beam. For each energy, the TLDs were irradiated in the dose range of 0–10 Gy in step of 2Gy. Regression analysis was performed to establish the response variation of thermoluminescent signals with dose and energy. Results The TLD-100 dose-response curves were obtained. In the dose range of 0–10 Gy, the calibration curve was confirmed to be linear for the conventional photon beam. In the same dose region, the quadratic model performs better than the linear model when high dose-per-pulse electron beams were used (F test; p<0.05). Conclusions This study demonstrates that the TLD dose response, for doses ≤10Gy, has a parabolic behavior in high dose-per-pulse electron beams. TLD-100 can be useful detectors for IOERT patient dosimetry if a proper calibration is provided.
Debt Management: Some Reflections Based on Argentina

A good liability management strategy is one that helps minimize the cost of borrowing over the medium and long term. The objective is not to save the last basis point in each transaction, but rather to bring down the overall borrowing cost. This paper uses Argentina's experience to illustrate some important elements in the design of a liability management strategy. It takes into account the specific characteristics of the Argentine capital market and of the debt instruments that are available.
Black Hole Entropy from BPS Closed String

By using BPS closed string, the entropy is calculated of the extremal five dimensional black hole consisting of Dirichlet onebranes, Dirichlet fivebranes and Kaluza-Klein momentum in the flat background approximation. In our formulations we consider two kinds of BPS closed strings with or without a winding number. In the former case heavy excitation modes of closed strings are used to derive the entropy. In the latter case we have no oscillator modes and consider collective motion of such massless closed strings. The entropy is given by the number of the ways how we divide the Kaluza-Klein momentum among the massless closed strings. In both cases the black hole entropy is the same as the Bekenstein-Hawking entropy. We argue that the collective modes of closed strings without winding is equivalent to a single closed string with winding. We propose that the two closed string pictures are connected with the open string pictures by the modular transformation.
Optimal Neuronal Tuning for Finite Stimulus Spaces

The efficiency of neuronal encoding in sensory and motor systems has been proposed as a first principle governing response properties within the central nervous system. We present a continuation of a theoretical study presented by Zhang and Sejnowski, where the influence of neuronal tuning properties on encoding accuracy is analyzed using information theory. When a finite stimulus space is considered, we show that the encoding accuracy improves with narrow tuning for one- and two-dimensional stimuli. For three dimensions and higher, there is an optimal tuning width.
Tumor necrosis factor/cachectin interacts with endothelial cell receptors to induce release of interleukin 1

Tumor necrosis factor/cachectin (TNF) has been implicated as a mediator of the host response in sepsis and neoplasia. Recent work has shown that TNF can modulate endothelial cell hemostatic properties, suggesting that endothelium is a target tissue for TNF. This led us to examine whether endothelial cells have specific binding sites for TNF and augment the biological response to TNF by elaborating the inflammatory mediator, IL-1. Incubation of 125I-recombinant human TNF with confluent, cultured human umbilical vein endothelial cells resulted in time-dependent, reversible, and saturable binding. Binding was half-maximal at a TNF concentration of 105 +/- 40 pM, and at saturation 1,500 molecules were bound per cell. Heat-treated TNF, which is biologically inactive, did not bind to endothelium. In addition to surface binding, TNF induced the elaboration of IL-1 activity by endothelial cells in a time-dependent manner. Generation of IL-1 activity required protein synthesis and was half-maximal at a TNF concentration of 50 +/- 20 pM. IL-1 activity from TNF-treated endothelium could be adsorbed by an immobilized antibody to IL-1. Heat- treated TNF was ineffective in eliciting endothelial cell IL-1. These data indicate that TNF can bind specifically to endothelium and initiate a cascade of inflammatory and coagulant events on the vessel surface potentially central to the host response to neoplasia and sepsis.
Sequence Peptide Qdm Absence of the MHC Class Ia Leader Dominant Peptide Bound To Qa-1 in the A Peptide from Heat Shock Protein 60 Is the

The MHC class Ib molecule Qa-1 binds speciﬁcally and predominantly to a single 9-aa peptide (AMAPRTLLL) derived from the leader sequence of many MHC class Ia proteins. This peptide is referred to as Qdm. In this study, we report the isolation and sequencing of a heat shock protein 60-derived peptide (GMKFDRGYI) from Qa-1. This peptide is the dominant peptide bound to Qa-1 in the absence of Qdm. A Qa-1-restricted CTL clone recognizes this heat shock protein 60 peptide, further verifying that it binds to Qa-1 and a peptide from the homologous Salmonella typhimurium protein GroEL (GMQFDRGYL). These observations have implications for how Qa-1 can inﬂuence NK cell and T cell effector function via the TCR and CD94/NKG2 family members, and how this effect can change under conditions that cause the peptides bound to Qa-1 to change. The Journal of Immunology, 2003, 170: 5027–5033.
Edge Detection of Synthetic Image Using GHM Multiwavelet Transform

--Edge detection has fundamental importance in image analysis. Classical edge detectors work only for specific image size and fail to operate on images with strong noise. Multiwavelets can achieve and maintain detail information of image well even in noisy environment. The steps involved in canny edge detector are performed in transformed domain (using DMWT) for synthetic image. Finally the performance is compared using FCR (False Correct Ratio).
WonGoo: a pure peer-to-peer full text information retrieval system based on semantic overlay networks

Compared with centralized information retrieval system, peer-to-peer (P2P) full text information retrieval system is more scalable, cost effective, fault tolerant, and powerful to search scarce content at the edge of Internet. However, P2P full text search is a very challenging problem, and the traditional broadcast ways are quite ineffective. We present a P2P full text information retrieval system WonGoo that is based on P2P structured overlay networks. We also implement a simulation program and test the performance of the system. Experimental results show that WonGoo is a steady system with high recall, good load balance and low resource usage.
Data Allocation Strategies for Dense Linear Algebra Kernels on Heterogeneous Two-dimensional Grids

We study the implementation of dense linear algebra computations, such as matrix multiplication and linear system solvers, on two-dimensional (2D) grids of heterogeneous processors. For these operations, 2D-grids are the key to scalability and efficiency. The uniform block-cyclic data distribution scheme commonly used for homogeneous collections of processors limits the performance of these operations on heterogeneous grids to the speed of the slowest processor. We present and study more sophisticated data allocation strategies that balance the load on heterogeneous 2D-grids with respect to the performance of the processors. The practical usefulness of these strategies is fully demonstrated by experimental data for a heterogeneous network of workstations.
Break CDK2/Cyclin E1 Interface Allosterically with Small Peptides

Most inhibitors of Cyclin-dependent kinase 2 (CDK2) target its ATP-binding pocket. It is difficult, however, to use this pocket to design very specific inhibitors because this catalytic pocket is highly conserved in the protein family of CDKs. Here we report some short peptides targeting a noncatalytic pocket near the interface of the CDK2/Cyclin complex. Docking and molecular dynamics simulations were used to select the peptides, and detailed dynamical network analysis revealed that these peptides weaken the complex formation via allosteric interactions. Our experiments showed that upon binding to the noncatalytic pocket, these peptides break the CDK2/Cyclin complex partially and diminish its kinase activity in vitro. The binding affinity of these peptides measured by Surface Plasmon Resonance can reach as low as 0.5 µM.
International Union of Pharmacology. XV. Subtypes of gamma-aminobutyric acidA receptors: classification on the basis of subunit structure and receptor function.

This article does not aim to review in detail the properties of γ-aminobutyric acidA(GABAA)breceptors, because recent accounts of that topic are available. In this same journal, a review of the binding properties and pharmacology of these receptors has been published ([Sieghart, 1995][1]). Other
Understanding Functional Reuse of ERP Requirements in the Telecommunication Sector: An Empirical Study

This paper is an empirical study on the application of Function Points (FP) and a FP-based reuse measurement model in Enterprise Resource Planning (ERP) projects in three organizations in the telecommunication sector. The findings of the study are used to compare the requirements reuse for one particular package, namely SAP. We found (1) that reuse is possible up to 80% at best, and (2) that, while for some modules, the organizations achieved the same levels of reuse, for other modules, the organizations' levels of reuse varied widely. We conclude with some implications of our findings for both practitioners and researchers.