Miracle-dz/UniFAR-FTUs huggingface dataset:
Author ' s personal copy How motivational orientation influences the evaluation and choice of hedonic and pragmatic interactive products : The role of regulatory focus

The perceived quality of interactive products can be roughly divided into instrumental, task-related, pragmatic attributes (e.g., usefulness, usability) and non-instrumental, self-referential, hedonic attributes (e.g., novelty, beauty). Recent studies suggest that the weighting of both aspects in forming an overall evaluation of an interactive product heavily depends on features of the actual situation, such as whether an individual has to perform a specific task or not. The present paper extends these findings by assuming that a match between an individual’s motivational orientation and particular product attributes (i.e., pragmatic, hedonic) moderates the perceived value of interactive products. Specifically, it shows how differences in regulatory foci (promotion or prevention focus), that is, differences in the way goal-directed behavior is regulated, influence product evaluation and choice. Participants were either set in a prevention focus (concern for safety and the avoidance of negative outcomes) or promotion focus (concern for personal growth and the attainment of positive outcomes). Subsequently, they were asked to evaluate and choose between a primarily pragmatic and a primarily hedonic mp3-player. The results revealed the expected effect of the activated regulatory focus on evaluation and choice. Individuals in a promotion focus rated the hedonic player as more appealing and chose it more frequently compared to individuals in a prevention focus. Reverse results, albeit not as strong, were found for the evaluation and choice of the pragmatic player. Our findings support the idea that product appeal and choice is strongly contextdependent. It further extends previous findings by showing that not only major differences in the situation, such as providing a specific task or not, impact product appreciation but that more subtle, motivational orientations can have similar effects. 2008 Elsevier B.V. All rights reserved.
Vehicular Ad-hoc Networks using slotted Aloha: Point-to-point, emergency and broadcast communications

The aim of this paper is to analyze the Aloha medium access (MAC) scheme in one-dimensional, linear networks, which might be an appropriate assumption for Vehicular Ad-hoc NET-works (VANETs). The locations of the vehicles are assumed to follow a homegeneous Poisson point process. Assuming power-law mean path-loss and independent point-to-point fading we study performance metrics based on the signal-over-interference and noise ratio (SINR). In contrast to previous studies where the receivers are at a fixed distance from the transmitter, we assume here that the receivers are the nearest neighbors of the transmitters in the Poisson process and in a given direction. We derive closed formulas for the capture probability and for the density of progress of a packet sent by a given node. We compute the mean delay to send a packet transmitted at each slot until successful reception. We also evaluate an upper bound to discover the neighborhood within a given space interval. We show that we can include noise in these models.
Fast, Warped Graph Embedding: Unifying Framework and One-Click Algorithm

What is the best way to describe a user in a social network with just a few numbers? Mathematically, this is equivalent to assigning a vector representation to each node in a graph, a process called graph embedding. We propose a novel framework, GEM-D that unifies most of the past algorithms such as LapEigs, DeepWalk and node2vec. GEM-D achieves its goal by decomposing any graph embedding algorithm into three building blocks: node proximity function, warping function and loss function. Based on thorough analysis of GEM-D, we propose a novel algorithm, called UltimateWalk, which outperforms the most-recently proposed state-of-the-art DeepWalk and node2vec. The contributions of this work are: (1) The proposed framework, GEM-D unifies the past graph embedding algorithms and provides a general recipe of how to design a graph embedding; (2) the nonlinearlity in the warping function contributes significantly to the quality of embedding and the exponential function is empirically optimal; (3) the proposed algorithm, UltimateWalk is one-click (no user-defined parameters), scalable and has a closed-form solution.
Effect of pulsed electromagnetic fields on the bioactivity of human osteoarthritic chondrocytes.

Low-frequency pulsed electromagnetic fields (PEMFs) are used for the treatment of human osteoarthritic cells in vivo without knowledge of underling principles. The authors evaluated the effect of PEMFs on human chondrocytes of the osteoarthritic knee in vitro. Biopsies of the cut femoral condyles after total knee arthroplasty were kept in a standard cell culture medium consisting of Dulbecco's modified Eagle's medium: nutrient mixture F-12, 10% fetal calf serum, PenStrept (Mediatech, Inc, Manassas, Virginia), and ascorbic acid for 4 days and randomly split into an exposed group (PEMF for 4 hours daily for 4 days at 75 Hz and 1.6 mT) and a control group. Both groups were retained for biochemical and polymerase chain reaction analysis (glycosaminoglycan and DNA levels). A P value less than . 05 was considered significant.DNA analysis revealed no differences between groups and no increase in content after exposure (P=.88 and .66, respectively). The increase of glycosaminoglycans was 0.4±1.6 ng (95% confidence interval [CI], 1.4 to 0.5) and -0.5±1.8 ng (95% CI, 0.6 to -1.5) in the exposed and control groups, respectively, with no significant difference (P=.24). A smaller decrease of glycosaminoglycan and DNA levels was observed over 4 days in the exposed group compared with the control group, with no statistical significance. The authors concluded that low-frequency PEMFs do not significantly influence the biosynthetic activity of explantcultures of human osteoarthritic cells in vitro. Nevertheless, they may be suitable as an adjuvant to a larger treatment regimen.
Dual-Layered Nanogel-Coated Hollow Lipid/Polypeptide Conjugate Assemblies for Potential pH-Triggered Intracellular Drug Release

To achieve effective intracellular anticancer drug delivery, the polymeric vesicles supplemented with the pH-responsive outlayered gels as a delivery system of doxorubicin (DOX) were developed from self-assembly of the lipid/polypeptide adduct, distearin grafted poly(γ-glutamic acid) (poly(γ-GA)), followed by sequential deposition of chitosan and poly(γ-GA-co-γ-glutamyl oxysuccinimide)-g-monomethoxy poly(ethylene glycol) in combination with in situ covalent cross-linking on assembly surfaces. The resultant gel-caged polymeric vesicles (GCPVs) showed superior performance in regulating drug release in response to the external pH change. Under typical physiological conditions (pH 7.4 and 37°C) at which the γ-GA/DOX ionic pairings remained mostly undisturbed, the dense outlayered gels of GCPVs significantly reduced the premature leakage of the uncomplexed payload. With the environmental pH being reduced from pH 7.4 to 4.7, the drug liberation was appreciably promoted by the massive disruption of the ionic γ-GA/DOX complexes along with the significant swelling of nanogel layers upon the increased protonation of chitosan chain segments. After being internalized by HeLa cells via endocytosis, GCPVs exhibited cytotoxic effect comparable to free DOX achieved by rapidly releasing the payload in intracellular acidic endosomes and lysosomes. This strongly implies the great promise of such unique GCPVs as an intracellular drug delivery carrier for potential anticancer treatment.
Game Theory Based Recommendation Mechanism for Taxi-Sharing

This paper presents a recommendation mechanism for taxi-sharing. The first aim of our model is to respectively recommend taxis and passengers for picking up passengers quickly and finding taxis easily. The second purpose is providing taxi-sharing service for passengers who want to save the payment. In our method, we analyze the historical Global Positioning System (GPS) trajectories generated by 10,357 taxis during 110 days and present the service region with time-dependent R-Tree. We formulate the problem of choosing the paths among the taxis in the same region by using non-cooperative game theory, and find out the solution of this game which is known as Nash equilibrium. The results show that our method can find taxis and passengers efficiently. In addition, applying our method can reduce the payment of passengers and increase the taxi revenue by taxi-sharing.
Does Smoothing Matter

We study how inhomogeneities modify large scale parameters in General Relativity. For a particular model, we obtain exact results: we compare an infinite string of extremal black holes to a corresponding smooth line with the same mass and charge in five dimensions. We find that the effective energy density doe s not differ significantly.
Cost of Institutional Harmonization in the ENP Countries

This paper analyzes the costs of (partial) institutional harmonization with the EU acquis which countries of the former USSR are expected to conduct under their Partnership and Cooperation Agreements with the EU and European Neighborhood Policy Action Plans. The public sector will have to take an effort of the transposition and adaptation of EU norms, as well as ensuring that they are complied with. Yet, the major part of the adjustment costs will fall on the private sector, as enterprises will have to make substantial investments to comply with new product requirements and business practices. In this study we used the method of extrapolation of average costs for CEE countries’ harmonization with acquis to estimate the potential harmonization costs for the neighboring countries based on internationally comparative macroeconomic indicators like sectoral and total value added. This involved estimating the EU pre-accession support for the CEE countries by main areas as a percentage of the total or sectoral value added, determining the expected degree of limited harmonization in the ENP countries and estimating 'coefficients of limited harmonization', which was subsequently used for adjustment of the estimated cost of full harmonization.
Access to Mathematics for Visually Disabled Students Through Multimodal Interaction

Mathematics relies on visual forms of communication and is thus largely inaccessible to people who cannot communicate in this manner because of visual disabilities. This paper outlines the Mathtalk project, which addresses this problem based on the use of computers to produce multi-modal renderings of mathematical information. This example is unusual in that it is essential to use multiple modalities because of the nature and the difficulty of the application. In addition, the emphasis is on non-visual and hence novel modalities. Access to mathematics 3
Despicable me(ter): Anonymous and fine-grained metering data reporting with dishonest meters

The Advanced Metering Infrastructure (AMI) is a fundamental component of modern Smart Grids, and allows fine-grained and real-time monitoring of the electricity consumption of utility customers. In an AMI, intelligent devices commonly called Smart Meters (SMs) communicate with an operation center for the purpose of management and billing. However, while on one hand this technology has the potential for advanced load balancing and grid management, it poses a threat to customers privacy. Indeed, an adversary can infer sensitive information about the end users by analyzing the metering data reported by the SMs. In this paper, we present the design of a privacy-preserving AMI for fine-grained metering data collection. We propose a collaborative protocol among SMs that achieves anonymous metering data delivery via a random multi-hop path. Our construction enables a verifier entity to detect any inconsistent behavior from SMs by accessing their internal log. Our scheme is scalable with the number of SMs in the network, and unlike existing methods, does not rely on trusted third-parties. We consider an adversarial setting where SMs are either honest-but-curious or controlled by a powerful adversary, whose aim is to deanonymize the received metering data. Finally, we prove that our protocol is secure and computationally efficient for the resource-constrained SM devices.
KOHONEN MAPS FOR PREDICTION OF BINDING TO HUMAN CYTOCHROME P450 3A4

The drug development process utilizes the parallel assessment of activity at a therapeutic target as well as absorption, distribution, metabolism, excretion, and toxicity properties of molecules. The development of novel, reliable, and inexpensive computational methods for the early assessment of metabolism and toxicity is becoming increasingly an important part of this process. We have used a computational approach for the assessment of drugs and drug-like compounds which bind to the cytochromes P450 (P450s) with experimentally determined Km values. The physicochemical properties of these compounds were calculated using molecular descriptor software and then analyzed using Kohonen self-organizing maps. This approach was applied to generate a P450-specific classification of nearly 500 drug compounds. We observed statistically significant differences in the molecular properties of low Km molecules for various P450s and suggest a relationship between 33 of these compounds and their CYP3A4-inhibitory activity. A test set of additional CYP3A4 inhibitors was used, and 13 of 15 of these molecules were colocated in the regions of low Km values. This computational approach represents a novel method for use in the generation of metabolism models, enabling the scoring of libraries of compounds for their Km values to numerous P450s.
Gmm-based Identification of Indonesian Speech

— This paper reports the performance of identification of Indonesian speech within a ten-Two types of experiments that have been undertaken: pair-wise and ten-language experiments. In the pair-wise experiments, the performance of the model in identifying Indonesian within every language pair is evaluated. The experiments show that Indonesian is best distinguished from English, Korean, and Portuguese with 90.5% of accuracy. In ten-language experiments, the highest accuracy of identifying Indonesian is 85.71%. I. INTRODUCTION Language identification is a task commonly performed on either text or speech. The aim is to identify the language (but not the actual words) of the text or speech. This paper focuses on language identification on speech, and on identifying Indonesian speech in particular. However, the technique transfers to the identification of other languages.
A Survey of Tree Convex Sets Test

Tree convex sets refer to a collection of sets such that each set in the collection is a subtree of a tree whose nodes are the elements of these sets. They extend the concept of row convex sets each of which is an interval over a total ordering of the elements of those sets. They have been applied to identify tractable Constraint Satisfaction Problems and Combinatorial Auction Problems. Recently, polynomial algorithms have been proposed to recognize tree convex sets. In this paper, we review the materials that are the key to a linear recognition algorithm.
KIBS Innovation Management Capability in Rural Portuguese Regions: Empirical Evidence

This article aims to evaluate the innovation management capacities of knowledge intensive business services (KIBS) and verify to what extent these companies return different profiles when classified by urban versus rural. Taking a sample of 500 KIBS, we applied a questionnaire with results revealing different explanatory variables for KIBS innovation capacities. From the set of five dimensions studied, factors relating strategy, learning, and network best explained rural versus urban KIBS innovation capacities.
Intelligent Deformable Organisms : An Artificial Life Approach to Medical Image Analysis

We propose and demonstrate a new paradigm for medical image analysis that borrows concepts from the field of artificial life. The paradigm prescribes intelligent agents in the form of artificial organisms whose primary objective is the proper segmentation and analysis of anatomical structures in medical images. An organism’s ‘awareness’ of the segmentation process guides it to identify landmark anatomical features during its development. The organism possesses a ‘brain’ enabling it to make decisions and issue ‘muscle’ actuation commands, resulting in shape deformations of its body, comprising skeleton and limbs. Behavioral decisions are based upon perceived data, memorized information, and a pre-stored ‘cognitive’ plan. The underlying medial-based representation of the organism’s bodily shape facilitates a variety of controlled deformations at multiple scales and locations. Our framework promises to lay the foundation for the construction of robust and automatic medical image analysis tools by combining deformable models and high-level a priori knowledge. We show how an intelligent corpus callosum agent, which takes the form of a worm, can deal with noise, incomplete edges, enormous anatomical variation, and occlusion in order to segment and label the corpus callosum in 2D mid-sagittal MRI slices of the brain.
Identification of the pre‐Bötzinger complex inspiratory center in calibrated “sandwich” slices from newborn mice with fluorescent Dbx1 interneurons

Inspiratory active pre‐Bötzinger complex (preBötC) networks produce the neural rhythm that initiates and controls breathing movements. We previously identified the preBötC in the newborn rat brainstem and established anatomically defined transverse slices in which the preBötC remains active when exposed at one surface. This follow‐up study uses a neonatal mouse model in which the preBötC as well as a genetically defined class of respiratory interneurons can be identified and selectively targeted for physiological recordings. The population of glutamatergic interneurons whose precursors express the transcription factor Dbx1 putatively comprises the core respiratory rhythmogenic circuit. Here, we used intersectional mouse genetics to identify the brainstem distribution of Dbx1‐derived neurons in the context of observable respiratory marker structures. This reference brainstem atlas enabled online histology for generating calibrated sandwich slices to identify the preBötC location, which was heretofore unspecified for perinatal mice. Sensitivity to opioids ensured that slice rhythms originated from preBötC neurons and not parafacial respiratory group/retrotrapezoid nucleus (pFRG/RTN) cells because opioids depress preBötC, but not pFRG/RTN rhythms. We found that the preBötC is centered ~0.4 mm caudal to the facial motor nucleus in this Cre/lox reporter mouse during postnatal days 0–4. Our findings provide the essential basis for future optically guided electrophysiological and fluorescence imaging‐based studies, as well as the application of other Cre‐dependent tools to record or manipulate respiratory rhythmogenic neurons. These resources will ultimately help elucidate the mechanisms that promote respiratory‐related oscillations of preBötC Dbx1‐derived neurons and thus breathing.
The role of phonetic and orthographic similarity in picture-word interference.

Picture-word interference refers to the fact that when a picture (i.e., line drawing) is presented with a word superimposed, picture-naming latency is longer than when the same picture is presented alone. This phe- nomenon, like the Stroop phenomenon, seems to be strongly influenced by the nature of the superimposed word. In the present paper the effects of phonetic and orthographic similarity between the word and the picture's name were investigated in order to get a clearer idea of the role these fac- tors play in the picture-naming process. Both orthographic and phonetic similarity were found to facilitate picture naming in comparison to an un- related word condition although not with respect to a picture alone condi- tion. Further, the data suggest that this facilitation is not an output phe- nomenon and, as such, can be separated from the response competition processes that lead to the basic interference effect. Instead, the locus of these effects appears to be the name-retrieval process with orthographic and phonetic information from the word aiding in the search for the picture's name. RESUME L'interference mot-image se rapporte au fait que lorsqu'une image (i.e., un dessin) est presentee avec un mot en surimpression, la latence d'i- dentification de I'image est plus longue que lorsque la meme image est presentee seule. Ce phenomene, comme celui de Stroop, semble etre for- tement influence par la nature du mot en surimpression. Les effets dus a la similitude phonetique et orthographiqu e existant entre le mot et le nom de I'image ont ete etudies dans le but de clarifier le role joue par ces facteurs dans le processus d'identification de I'image. Les similitudes orthogra- phiques et phonetiques facilitent toutes deux ('identification de I'image comparativement a la condition ou un mot non relie est utilise mais non par rapport a la situation ou I'image seule doit etre identifiee. De plus, les donnees suggerent que cette facilitation n'est pas liee a la sortie de I'infor- mation et peut, en ce sens, etre dissociee des processus de competition de la reponse qui conduisent a I'effet d'interference. Les effets trouves resi- deraient plutot dans le processus de recouvrement du mot dont la simili- tude orthographique et phonetique favorise la recherche du nom de I'image.
Rationality in Decision Machines

This brief position paper 1 sketches a view, in many respects conventional, of the role of rationality in artificial intelligence. In this view, rationality is primarily a way to describe coherence between actions and agent attitudes such as belief and preference. Decisions are the fundamental unit of calculation for a rational computer, and therefore we properly refer to them as decision machines. Collections of interacting decision machines, or decision factories , should not in general be expected to be rational, although we should exploit the rationality of their constituent machines in configuring decision factories.
An ensemble learning algorithm based on Lasso selection

Ensemble learning, especially selective ensemble learning is now becoming more and more popular in the field of machine learning. This paper introduces a new ensemble algorithm, named Lasso-Bagging Trees ensemble algorithm. This algorithm is in order to improve the whole learning ability, which is a combination of tree predictors and this method chooses and ensembles trees based on the shrinkage estimation of lasso technology. Compared with a series of other learning algorithms, it demonstrates better generalization ability and higher efficiency.
Deformation invariant attribute vector for 3D image registration: method and validation

This paper proposes a novel method to define deformation invariant attribute vector for each voxel in 3D image for the purpose of anatomic correspondence detection. This is the extension of the work for 2D deformation invariant attribute using geodesic intensity histogram (GIH). Our original contribution is to extend this 2D technique to 3D image, and validate the method using synthesized deformation in 3D brain MRI image. Both theoretic analysis and initial validation result show that the proposed attribute vector is invariant to deformation. This deformation invariant attribute vector has wide applications in registration of 3D medical images