Miracle-dz/UniFAR-FTUs huggingface dataset:
Framework for NFC-Based Intelligent Agents: A Context-Awareness Enabler for Social Internet of Things

Context-aware applications are required to be aware of user context and ambient intelligent to support nonintrusive human-computer interaction. However, the uncertain real-world environments make it difficult for a system to perceive enough environmental contexts and achieve user's goal. Therefore, this study proposes a framework for developing an NFC-enabled intelligent agent, which combines the NFC technique with context-acquisition, ontology-knowledgebase, and semantic-adaptation modules to be aware of location, time, device, and activity contexts with respect to personal and social profiles. To cope with the uncertain environment, a credit-based incentive scheme is also proposed to encourage social cooperation and thereby enlarge the value of personal perceptions. By developing a complete ontology knowledgebase, the proposed framework can incorporate with social-cooperation schemes to recommend relevant services for supporting reactive action, proactive achievement, and social cooperation. The resultant social-advertising system shows that this framework can support a wide-range of different functionalities and is indispensable to an NFC-based intelligent agent for social Internet of things.
Network Dimensioning Based on Percentage of Access Link Capacity Carrying Premium Traffic

Network dimensioning is typically based on a traffic matrix that contains the bandwidth demand for each source-destination pair. We consider a different approach, which assumes that only the maximum amount of premium traffic that can be carried across each access link is known. Based on this information, we present three algorithms for determining the bandwidth required for premium traffic in the core network. The first algorithm intermediately estimates the traffic matrix based on the "gravity model". The other two algorithms compute the worst-case requirements for premium traffic when there are no link failures and fixed routing is used (second algorithm), and when there are link failures and alternative routing paths are available (third algorithm). An important feature of the two worst-case algorithms is that they allow admission control decisions to be based solely on the availability of bandwidth for premium traffic at the access links. We apply and compare the three algorithms for the Greek Research and Technology Network (GRNET), which currently uses the third algorithm for its premium IP service.
Video shots retrieval using local invariant features

In this paper, we present an efficient video shots retrieval system based on local feature detection, description and matching. A face tracker is first used to obtain information on faces in different viewpoints. A visual vocabulary is built off-line using an invariant descriptor computed on tracked character face regions in all shots. The vocabulary is refined in two ways to make the retrieval system more efficient. Firstly, the visual vocabulary is minimized by only using facial features selected on face regions which are detected by an accurate face detector. Secondly, three criteria, namely Inverted-Occurrence-Frequency Weights, Average Feature Location Distance and Reliable Nearest-Neighbors, are calculated in advance to make the on-line retrieval procedure more efficient and precise. The proposed system is experimented on the movie "Groundhog Day". The results show that our technique is very effective and efficient on video shots retrieval.
SNAP-25 Is Targeted to the Plasma Membrane through a Novel Membrane-binding Domain*

SNAP-25, syntaxin, and synaptobrevin are SNARE proteins that mediate fusion of synaptic vesicles with the plasma membrane. Membrane attachment of syntaxin and synaptobrevin is achieved through a C-terminal hydrophobic tail, whereas SNAP-25 association with membranes appears to depend upon palmitoylation of cysteine residues located in the center of the molecule. This process requires an intact secretory pathway and is inhibited by brefeldin A. Here we show that the minimal plasma membrane-targeting domain of SNAP-25 maps to residues 85–120. This sequence is both necessary and sufficient to target a heterologous protein to the plasma membrane. Palmitoylation of this domain is sensitive to brefeldin A, suggesting that it uses the same membrane-targeting mechanism as the full-length protein. As expected, the palmitoylated cysteine cluster is present within this domain, but surprisingly, membrane anchoring requires an additional five-amino acid sequence that is highly conserved among SNAP-25 family members. Significantly, the membrane-targeting module coincides with the protease-sensitive stretch (residues 83–120) that connects the two α-helices that SNAP-25 contributes to the four-helix bundle of the synaptic SNARE complex. Our results demonstrate that residues 85–120 of SNAP-25 represent a protein module that is physically and functionally separable from the SNARE complex-forming domains.
Social Influence in the online Recruitment of terrorists and terrorist Sympathizers: Implications for Social Psychology Research

Resume Depuis sa creation, les gens ont toujours trouve des methodes de communication nouvelles et inattendues via l’Internet. L’une de ces pratiques a ete le recrutement de nouveaux membres par des organisations terroristes comme Al Qaeda (Riedel, 2007). Al-Qaeda utilise des techniques d’influence sociale pour inciter les individus a devenir sympathisants des terroristes (Burton & Stewart, 2008 ; Gerwehr & Daly, 2005 ; Al-Saleh, 2007). En commencant par de simples demandes en ligne, puis en augmentant progressivement l’engagement a une cause, l’organisation terroriste peut influencer ses cibles afin qu’elles soutiennent des ideologies bien plus extremes qu’elles ne l’auraient fait. A l’image de ce que propose la theorie de l’auto-perception (Bem, 1972), les nouveaux convertis peuvent se forger des attitudes de plus en plus radicales consistantes avec leurs comportements qui se radicalisent. Le renforcement de la saillance de l’identite sociale d’appartenance a un groupe peut egalement amplifier l’influence de telles techniques de recrutement. Les implications pour la recherche sur l’influence sociale dans le recrutement en ligne des terroristes sont discutees.
Expression of leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1) on osteoclasts and its potential role in rheumatoid arthritis

OBJECTIVE: Leukocyte-associated immunoglobulin-like receptor-1 is an inhibitory receptor primarily expressed by immune cells. This study was undertaken to define the role of this molecule in osteoclast differentiation and rheumatoid arthritis. METHODS: In vitro osteoclast assays were performed to characterize the role of Leukocyte-associated immunoglobulin-like receptor-1 in murine and human osteoclastogenesis. Human Leukocyte-associated immunoglobulin-like receptor-1 expression was assessed by immunohistochemistry staining in the synovium of patients with rheumatoid arthritis. The levels of soluble Human Leukocyte-associated immunoglobulin-like receptor-1 were determined by enzyme-linked immunosorbent assay. RESULTS: We found that multinucleated osteoclast formation from mouse bone marrow cells was inhibited by treatment with a monoclonal antibody against mouse Leukocyte-associated immunoglobulin-like receptor-1 in vitro. By immunohistochemistry, we found that Leukocyte-associated immunoglobulin-like receptor-1 was mainly expressed by macrophages in the inflamed synovial tissue of rheumatoid arthritis patients. In addition, serum and synovial fluid levels of soluble Leukocyte-associated immunoglobulin-like receptor-1 were higher in rheumatoid arthritis patients compared to healthy controls or osteoarthritis patients. Moreover, overexpression of Leukocyte-associated immunoglobulin-like receptor-1 in CD14+ monocytes from healthy volunteers also inhibited human osteoclastogenesis. CONCLUSION: Collectively, these data demonstrate for the first time that Leukocyte-associated immunoglobulin-like receptor-1 inhibits osteoclastogenesis. Therefore, these results may have therapeutic implications for the treatment of rheumatoid arthritis.
On Secure Wireless Communications for IoT Under Eavesdropper Collusion

Wireless communication is one of the key technologies that actualize the Internet of Things (IoT) concept into the real world. Understanding the security performance of wireless communications lays the foundation for the security management of IoT. Eavesdropper collusion represents a significant threat to wireless communication security, while physical-layer security serves as a promising approach to providing a strong form of security guarantee. This paper studies the important secrecy outage performance of wireless communications under eavesdropper collusion, where the physical layer security is adopted to counteract such attack. Based on the classical Probability Theory, we first conduct analysis on the secrecy outage of the simple noncolluding case in which eavesdroppers do not collude and operate independently. For the secrecy outage analysis of the more hazardous M-colluding scenario, where any M eavesdroppers can combine their observations to decode the message, the techniques of Laplace transform, keyhole contour integral, and Cauchy Integral Theorem are jointly adopted to work around the highly cumbersome multifold convolution problem involved in such analysis, such that the related signal-to-interference ratio modeling for all colluding eavesdroppers can be conducted and thus the corresponding secrecy outage probability can be analytically determined. Finally, simulation and numerical results are provided to illustrate our theoretical achievements. An interesting observation suggests that the SOP increases first superlinearly and then sublinearly with M.
Model for Discovering Students' Skills in Educational Institutions

Discovering and sharing knowledge is considered to be a challenge faced by every modern academic institution. Recent research results have emphasized the fact that student skills and competencies cannot be measured in a simple way. Therefore, in this paper we present a list of parameters for discovering knowledge, based on available materials and human resources. The main goal of our research is to define an implementable model for measuring student skills and competencies in a real educational environment. Our model eliminates emerged shortcomings from our previous experience in working with distance learning platform and promises good results.
Is there chaos in the brain?

Abstract For some years there has been a controversy about whether brain state variables such as EEG or neuronal spike trains exhibit chaotic behaviour. Wright & Liley claim that the local dynamics measured by spike trains or local field potentials exhibit chaotic behaviour, but global measures like EEG should be governed by linear dynamics. We propose a different scheme. Based on simulation studies and various experiments, we suggest that the pointwise dimension of EEG time series may provide some valuable information about underlying neuronal generators.
The Valuation of Nursing Begins With Identifying Value Drivers

Adequate investment in a profession links to its ability to define and document its value. This requires identifying those elements or value drivers that demonstrate its worth. To completely identify nursing's value drivers requires meshing the economic, technical, and caring aspects of its profession. Nursing's valuation includes assessing nursing's tangible and intangible assets and documenting these assets. This information communicates nursing's worth and ensures adequate economic investment in its services.
Structure of the Jackson Personality Inventory from the Perspective of the Five-Factor Model

The generality and comprehensiveness of the five-factor model was tested using the Jackson Personality Inventory. The Interpersonal Adjective Scales Revised-B5 and the NEO Five-Factor Inventory scales were used as markers for the five-factor model. 220 introductory psychology students (104 men and 116 women) voluntarily completed the three inventories for partial course credit. Combined factor analysis of the 25 scales from the three inventories yielded six major factors. Five of these factors were similar to the five major factors of personality, namely, Extraversion, Neuroticism, Openness, Agreeableness, and Conscientiousness, and the sixth factor was identified as Social Adroitness. These results supported the generality but not the comprehensiveness of the five-factor model.
The more things change, the more they stay the same: explaining stratification within the Faculty of Advocates, Scotland

Since the 1970s the legal profession has become increasingly diversified. However, the inclusion of traditionally excluded social groups has not eradicated inequalities. This paper attempts to explain the contradiction between increasing diversification and persistence of inequalities by examining changes in the structure of the Faculty of Advocates in Scotland. We observe significant changes over the last 40 years, especially the increasing numbers of women entering the Faculty. Yet, women still face discrimination, and their success has largely been at the expense of working-class aspirants. We argue that existing theoretical perspectives, namely feminism and the perspectives of Bourdieu, as well as new insights offered by Beck, are insufficient to account for stratification within the legal profession. We call for a new theoretical perspective which accounts for both social change and persistence of inequalities, and suggest that such an approach is best offered by a feminist reworking of Bourdieu.
Similarities and varieties in human motion trajectories of predefined grasping and disposing movements

Human movement is characterized by smoothed trajectories and individual solutions relating to joint angle configuration. For the transformation of human movement characteristics into humanoid robots knowledge about basic strategies and the nature of human motion is necessary. The objective of this study is the inter-individual and intra-individual comparison of movement trajectories and time series of joint angles for several predefined object manipulations. For that purpose the kinematics of arm, hand and finger motion was measured via 3D video motion capturing and analyzed. Graphs of object trajectories, joint angles and finger tip distances (grasp state) were displayed for an example motion: moving to a cuboid, grasping the object and putting it to a heightened target position. The varieties in motion of different subjects and within repeated motion cycles of one and the same subject are presented. Besides this we show, how test subjects with different body height solve the motion task.
MRtrix: Diffusion tractography in crossing fiber regions

In recent years, diffusion‐weighted magnetic resonance imaging has attracted considerable attention due to its unique potential to delineate the white matter pathways of the brain. However, methodologies currently available and in common use among neuroscientists and clinicians are typically based on the diffusion tensor model, which has comprehensively been shown to be inadequate to characterize diffusion in brain white matter. This is due to the fact that it is only capable of resolving a single fiber orientation per voxel, causing incorrect fiber orientations, and hence pathways, to be estimated through these voxels. Given that the proportion of affected voxels has been recently estimated at 90%, this is a serious limitation. Furthermore, most implementations use simple “deterministic” streamlines tracking algorithms, which have now been superseded by “probabilistic” approaches. In this study, we present a robust set of tools to perform tractography, using fiber orientations estimated using the validated constrained spherical deconvolution method, coupled with a probabilistic streamlines tracking algorithm. This methodology is shown to provide superior delineations of a number of known white matter tracts, in a manner robust to crossing fiber effects. These tools have been compiled into a software package, called MRtrix, which has been made freely available for use by the scientific community. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 53–66, 2012
Two-stage segmentation for detection of suspicious objects in aerial and long-range surveillance applications

This paper presents a novel two-stage data segmentation approach for detection of artificial materials and objects in non-urban terrain. High resolution image of the unknown terrain taken with the digital camera from relatively large distance is divided into smaller sub-images for further processing. Each sub-image is segmented and information about obtained cluster centers is transferred to the next stage. Second segmentation stage uses information about cluster centers from all sub-images and applies the same clustering method to this data set. Finally, decision-making module evaluates all potential candidate segments and eventually proposes segments that have high possibility of presenting artificial material or object in the input image.
The Importance of Rule Restrictions in CCG

Combinatory Categorial Grammar (CCG) is generally construed as a fully lexicalized formalism, where all grammars use one and the same universal set of rules, and cross-linguistic variation is isolated in the lexicon. In this paper, we show that the weak generative capacity of this 'pure' form of CCG is strictly smaller than that of CCG with grammar-specific rules, and of other mildly context-sensitive grammar formalisms, including Tree Adjoining Grammar (TAG). Our result also carries over to a multi-modal extension of CCG.
Shifts in Lake N:P Stoichiometry and Nutrient Limitation Driven by Atmospheric Nitrogen Deposition

Nitrogen Overload The cycling of essential nutrients in terrestrial ecosystems has been altered by human activities. Elser et al. (p. 835) report a comparative analysis of lakes in Norway, Sweden, and in the United States that suggests that this is also true in aquatic ecosystems such as lakes. Deposition of anthropogenically derived atmospheric nitrogen controls whether N or P is growth-limiting for phytoplankton. Under elevated conditions of atmospheric N inputs, lake phytoplankton become consistently P-limited because the N:P ratio is strongly distorted. This is in contrast to conditions of low N deposition when lake phytoplankton are N-limited. These effects are even observed in remote lakes, demonstrating the indirect yet wide-ranging effects of humans on global food webs. Deposition of anthropogenically derived nitrogen can cause phosphorus to become the limiting nutrient of lake phytoplankton. Human activities have more than doubled the amount of nitrogen (N) circulating in the biosphere. One major pathway of this anthropogenic N input into ecosystems has been increased regional deposition from the atmosphere. Here we show that atmospheric N deposition increased the stoichiometric ratio of N and phosphorus (P) in lakes in Norway, Sweden, and Colorado, United States, and, as a result, patterns of ecological nutrient limitation were shifted. Under low N deposition, phytoplankton growth is generally N-limited; however, in high–N deposition lakes, phytoplankton growth is consistently P-limited. Continued anthropogenic amplification of the global N cycle will further alter ecological processes, such as biogeochemical cycling, trophic dynamics, and biological diversity, in the world’s lakes, even in lakes far from direct human disturbance.
In vivo isolation of the effects of melanin from underlying hemodynamics across skin types using spatial frequency domain spectroscopy

Abstract. Skin is a highly structured tissue, raising concerns as to whether skin pigmentation due to epidermal melanin may confound accurate measurements of underlying hemodynamics. Using both venous and arterial cuff occlusions as a means of inducing differential hemodynamic perturbations, we present analyses of spectra limited to the visible or near-infrared regime, in addition to a layered model approach. The influence of melanin, spanning Fitzpatrick skin types I to V, on underlying estimations of hemodynamics in skin as interpreted by these spectral regions are assessed. The layered model provides minimal cross-talk between melanin and hemodynamics and enables removal of problematic correlations between measured tissue oxygenation estimates and skin phototype.
Incremental Learning of Statistical Motion Patterns With Growing Hidden Markov Models

Modeling and predicting human and vehicle motion is an active research domain. Due to the difficulty of modeling the various factors that determine motion (e.g., internal state and perception), this is often tackled by applying machine learning techniques to build a statistical model, using as input a collection of trajectories gathered through a sensor (e.g., camera and laser scanner), and then using that model to predict further motion. Unfortunately, most current techniques use offline learning algorithms, meaning that they are not able to learn new motion patterns once the learning stage has finished. In this paper, we present an approach where motion patterns can be learned incrementally and in parallel with prediction. Our work is based on a novel extension to hidden Markov models (HMMs) - called growing hidden Markov models - which gives us the ability to incrementally learn both the parameters and the structure of the model.
A genetic algorithm for register allocation

In this paper we introduce a new genetic algorithm for register allocation. A merge operator is used to generate new individual solutions. The number of steps required to examine all pairs in the population matrix to generate n/sup 2/ (n is the population matrix size). Generating an offspring from the parents needs m steps (m number of nodes). The total number of steps required by the algorithm is n/sup 2/m, that is the genetic algorithm has a linear time complexity in terms of number of nodes. The experimental results show optimal solutions in many of the graphs used for testing.
Coulomb Explosion Imaging of Small Molecules

Most of our knowledge of the structures of free molecules comes from indirect observations that focus on other properties (for example, energy or mass spectra) that depend on structure. Recently, a new method has been developed that instead yields geometrical images of individual molecules. This method takes advantage of the large Coulomb repulsion of the nuclei within molecules rapidly stripped of their electrons. The first experiments with this new technique have already revealed structural images of several important species, such as positively charged methane ions.
What Is the Strategic Role of Online Newspapers?

Abstract The newspapers are in a pressed situation of circulation decline. This is partly a consequence of increased Internet usage, a development the papers themselves have helped push forward. This survey reveals that Norwegian newspapers executives do not approve fully of their own organizations’ online activities, and explores their rationale for online publishing: Is it marketing of the print product, the development of new business, or are the newspapers still in an explorative mode?