Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative study of some algorithms for detecting communities in social networks

In this paper, we studied some methods used in community detection in social networks. In the context of social networks, a community is a set of entities with a lot of interactions among them and little interaction with other sets outside. There are approaches related to static social networks, and others which focus on the dynamic social networks whose structure (actors and links) evolves over time. Static community detection approaches are able to find a division only if a graph is defined for a given time. However, many real graphs have the property to change and evolve over time. That is some nodes and links can appear or disappear during this process of evolution. In order to find communities in such networks we must take into account their different stages of evolution to provide coherent communities not just in a particular point in time, but all along their possible modifications over time. In this paper, we studied the static and dynamic approaches and we made a comparison between different algorithms using several real datasets.
A Dynamic Programming Algorithm for Joint VNF Placement and Chaining

This paper addresses the problem of Virtualized Network Functions placement and traffic steering in Cloud infrastructures. We design an efficient dynamic programming (DP) algorithm for joint VNF placement and traffic steering that runs in polynomial time. In compliance with dynamic programming approaches, we organize the problem in smaller interdependent subproblems (one per VNF in the requested chain) that are solved successively and aggregated to compose the overall chain placement. We demonstrate the potential of our solution by comparing it with a Multi-Stage approach and a greedy algorithm. Simulation results show that our dynamic programming algorithm achieves better performance in terms of resource usage, acceptance rate and cloud provider revenue.
Scalability in an adaptive cooperative system for wireless sensor networks

The performance of wireless sensor networks (WSNs) can be significantly improved using adaptive cooperative diversity (SCA) technique, which is basically a cross-layer design that combines truncated ARQ at the link layer and cooperative diversity at the physical layer. LEACH is a protocol for wireless sensor networks that utilizes randomized rotation of local cluster heads to evenly distribute the energy load among the sensors in the network. This paper proposes and evaluates the performance of a selective cooperative scheme for wireless sensor networks based on scalability. The evaluation of the lifetime and packet loss rate is presented and results based on the maximum number of retransmissions, network size, packet length and initial energy by nodes are provided. Our scheme shows better performance as compared to others.
A Kinect-sensor-based Tracked Robot for Exploring and Climbing Stairs

This paper focuses on the stair-climbing problem for a tracked robot. The tracked robot designed in this paper has the ability to explore stairs in an unknown indoor environment, climbing up and down the stairs, keeping balance while climbing, and successfully landing on the stair platform. Intelligent algorithms are proposed to explore and align stairs, and a fuzzy controller is introduced to stabilize the tracked robot's movement during the exploration. An inexpensive Kinect depth sensor is the only equipment needed for all the control modes. Finally, experiments illustrate the effectiveness of the proposed approach for climbing stairs.
Progesterone Receptor Activates Msx2 Expression by Downregulating TNAP/Akp2 and Activating the Bmp Pathway in EpH4 Mouse Mammary Epithelial Cells

Previously we demonstrated that EpH4 mouse mammary epithelial cells induced the homeobox transcription factor Msx2 either when transfected with the progesterone receptor (PR) or when treated with Bmp2/4. Msx2 upregulation was unaffected by Wnt inhibitors s-FRP or Dkk1, but was inhibited by the Bmp antagonist Noggin. We therefore hypothesized that PR signaling to Msx2 acts through the Bmp receptor pathway. Herein, we confirm that transcripts for Alk2/ActR1A, a non-canonical BmpR Type I, are upregulated in mammary epithelial cells overexpressing PR (EpH4-PR). Increased phosphorylation of Smads 1,5, 8, known substrates for Alk2 and other BmpR Type I proteins, was observed as was their translocation to the nucleus in EpH4-PR cells. Analysis also showed that Tissue Non-Specific Alkaline Phosphatase (TNAP/Akp2) was also found to be downregulated in EpH4-PR cells. When an Akp2 promoter-reporter construct containing a ½PRE site was transfected into EpH4-PR cells, its expression was downregulated. Moreover, siRNA mediated knockdown of Akp2 increased both Alk2 and Msx2 expression. Collectively these data suggest that PR inhibition of Akp2 results in increased Alk2 activity, increased phosphorylation of Smads 1,5,8, and ultimately upregulation of Msx2. These studies imply that re-activation of the Akp2 gene could be helpful in downregulating aberrant Msx2 expression in PR+ breast cancers.
Type III Secretion System Genes in Clinical Aeromonas Isolates

ABSTRACT We have identified the genes ascF and ascG, which encode components of a putative type III secretion system (TTSS) in Aeromonas. We investigated the distribution of these and other TTSS genes in 84 clinical isolates and found hybridizing sequences in 50% of the strains, with a higher prevalence in Aeromonas hydrophila and Aeromonas veronii than in Aeromonas caviae.
Impr ovementof Linear Discriminant Analysis by Applying The EnsembleMethod Content Ar eas : machinelearning , computational complexity

Linear DiscriminantAnalysis(LDA) is oneof the learningalgorithmsfor the binary problems. One of the drawbacksof LDA is the degradationof its performancewhenit is difficult to approximatethe boundarybetweentwo classeswith a linear function, i.e. the boundaryis non-linear . In this research,we apply Error-CorrectingOutput Codes (ECOC) to LDA. ECOCis well-known asoneof the ensemblemethods. Further, we introducethe weighted voting method to reducethe influence of poor hypotheseson the classificationaccuracy. The hypothesesare weighted accordingto their classificationaccuracy. Moreover, althoughLDA wasoriginally designedfor applyingto only binary classificationproblems,it can be extendedto the multi-classproblemsby introducingECOC.
A Low Cost Tactor Suit for Vibrotactile Feedback

We constructed low cost tactors for vibrotactile feedback across the human arm for the purpose of providing a physical sensation surrogate for virtual objects. The tactors were built from readily available commercial parts, and provide low amplitude vibration for tactile feedback. The tactors are Velcro mounted on a custom suit designed to ensure localized sensations of each tactor. The suit is designed to be compatible with standard motion capture devices. Our suit provides 24 vibratory tactors in a tactor array on the user’s right arm and hand, and can easily be expanded to include the entire torso and body. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-03-44. This technical report is available at ScholarlyCommons: https://repository.upenn. edu/cis_reports/66 A Low Cost Tactor Suit for Vibrotactile Feedback Aaron Bloomfield Norman I. Badler Center for Human Modeling and Simulation University of Pennsylvania {aaronb, badler } @cis.upenn. edu
Origins of socio-economic inequalities in cancer survival: a review.

BACKGROUND Cancer survival is known to vary by socio-economic group. A review of studies published by 1995 showed this association to be universal and resilient to the many different ways in which socio-economic status was determined. Differences were most commonly attributed to differences in stage of disease at diagnosis. MATERIALS AND METHODS A review of research published since 1995 examining the association of cancer survival with socio-economic variables. RESULTS An association between socio-economic status and cancer survival has continued to be demonstrated in the last decade of research. Stage at diagnosis and differences in treatment have been cited as the most important explanatory factors. Some research has evaluated the psychosocial elements of this association. CONCLUSIONS Socio-economic differences in cancer survival are now well documented. The explanatory power of stage at diagnosis, although great, should not detract from the evidence of differential treatment between social groups. Neither factor can completely explain the observed socio-economic differences in survival, however, and the importance of differences in tumour and patient factors should now be quantified.
Fractional Recall: Understanding Forgetting of Mathematics Learning from Computer Assisted Instruction Data and Implications for Personalized Learning in Low Resource Contexts

Author(s): Tibbles, Richard | Advisor(s): Jernigan, Terry | Abstract: Recent work in forgetting and spacing of learning across long time scales suggests that which has been learned is easily forgotten. In order to be able to prevent this forgetting from happening in educational contexts, it is useful to understand how this forgetting occurs outside of the laboratory. Analyses are conducted of the time course of forgetting for declarative fact and Mathematics learning from computer assisted instruction systems, in order to see how forgetting occurs in ecologically valid contexts. The difference between the learning of declarative facts and Mathematics skills is compared and contrasted, showing that individual Mathematics questions behave similarly to fact learning, but that the learning of Mathematics skills may potentially have differing long term trajectories.
Instability phenomena in underloaded packet networks with QoS schedulers

Instability in packet-switching networks is normally associated with overload conditions, since queueing network models show that, in simple configurations, only overload generates instability. However, some results showing that instability can happen also in underloaded queueing networks appeared in the recent literature. Underload instabilities can be produced by complex scheduling algorithms, that bear significant resemblance to the Quality of Service (QoS) schedulers considered today for packet networks. In this paper, we study with fluid models and with adversarial queueing theory possible underload instabilities due to strict-priority schedulers and to Generalized Processor Sharing (GPS) schedulers.
Who do they think we are? Public perceptions of psychiatrists and psychologists

ABSTRACT Objective: Psychiatrists and clinical psychologists assess and treat individuals with a wide-range of mental health needs, and the differences between them are not always well understood by other professionals or the public. Most work on perceptions in mental health has evaluated issues such as diagnosis, risk, prognosis, and blame. Little has evaluated and contrasted broader perceptions of psychiatrists and psychologists. We qualitatively explored views of members of the public, in order to identify such wider understanding. Method: Nine individuals with no experience of mental ill-health were interviewed using a semi-structured interview guide. Transcripts were thematically analysed. Results: Three core themes were identified: perception of roles, stigma, and increasing future awareness. There was frequent misunderstanding of these professions. In general, however, psychiatrists were seen as more authoritarian and with a medication focus, though their interventions were believed to be effective. Psychologists were perceived as friendlier and having a better rapport, though participants thought they only typically looked at ‘minor’ difficulties. Discussion: Public perceptions matter. There is a lack of clarity in the public mind about our roles. These data should aid professionals’ self-reflection of potential transference issues, and to consider local applicability and variation of our findings. The two professions should consider public psychoeducatative programmes to inform and encourage engagement. Video abstract Read the transcript Watch the video on Vimeo
Interpolation-based image inpainting in color images using high dimensional model representation

Image inpainting is the process of filling missing or fixing corrupted regions in a given image. The intensity values of the pixels in missing area are expected to be associated with the pixels in the surrounding area. Interpolation-based methods that can solve the problem with a high accuracy may become inefficient when the dimension of the data increases. We solve this problem by representing images with lower dimensions using High Dimensional Model Representation method. We then perform Lagrange interpolation on the lower dimensional data to find the intensity values of the missing pixels. In order to use High Dimensional Model Representation method and to improve the accuracy of Lagrange interpolation, we also propose a procedure that decompose missing regions into smaller ones and perform inpainting hierarchically starting from the smallest region. Experimental results demonstrate that the proposed method produces better results than the variational and exemplar-based inpainting approaches in most of the test images.
Analysis of Gate Leakage Current in IP3 SRAM Bit-Cell under Temperature Variations in DSM Technology

In this paper, we present the temperature based simulation and analysis of gate leakage current for the proposed low-stress IP3 SRAM bit cell. In CMOS technologies, cache memory occupies a large die area and this may experience different temperatures. Under temperature variations, performance of the system may degrade. Therefore, in the IP3 SRAM cell, gate leakage has been analyzed under temperature variations. It is observed that with rise in temperature, leakage and standby power dissipation increases. The observation of the effect of temperature variations on standby power indicates that increase in standby power is minimum for P3 cell and IP3 cell, with respect to 6T and PP SRAM cells. The gate leakage observed is minimum in IP3 cell with temperature variations. This work is being carried out at deep-sub micron CMOS technology, 45nm, with tox=2.4nm, Vthn=0.22V, Vthp=0.224V, VDD=0.7V and temperature is varied from -25 0 C to +125 0 C.
Disk Evolution and Bar Triggering Driven by Interactions with Dark Matter Substructure

We study formation and evolution of bar-disk systems in fully self-consistent cosmological simulations of galaxy formation in the ΛCDM WMAP3 universe. In a representative model we find that the first generation of bars form in response to the asymmetric dark matter (DM) distribution (i.e., DM filament) and quickly decay. Subsequent bar generations form and are destroyed during the major merger epoch permeated by interactions with a DM substructure (subhalos). A long-lived bar is triggered by a tide from a subhalo and survives for ~10 Gyr. The evolution of this bar is followed during the subsequent numerous minor mergers and interactions with the substructure. Together with intrinsic factors, these interactions largely determine the stellar bar evolution. The bar strength and its pattern speed anticorrelate, except during interactions and the formation of a secondary (nuclear) bar. For about 5 Gyr bar pattern speed increases substantially despite the loss of angular momentum to stars and cuspy DM halo. We analyze the evolution of stellar populations in the bar-disk and relate them to the underlying dynamics. While the bar is made mainly of an intermediate age, ~5-6 Gyr, disk stars at z = 0, a secondary nuclear bar which surfaces at z ∼ 0.1 is made of younger, ~1-3 Gyr stars.
In Vitro Metabolism of 2-[6-(4-Chlorophenyl)-2,2-dimethyl-7-phenyl-2,3-dihydro-1H-pyrrolizin-5-yl] Acetic Acid (Licofelone, ML3000), an Inhibitor of Cyclooxygenase-1 and -2 and 5-Lipoxygenase

2-[6-(4-Chlorophenyl)-2,2-dimethyl-7-phenyl-2,3-dihydro-1H-pyrrolizin-5-yl] acetic acid (licofelone) is a dual inhibitor of both cyclooxygenase isoforms and 5-lipoxygenase and under development for treatment of osteoarthritis. In conventional in vitro assays using liver microsomes and NADPH as cosubstrate, a high metabolic stability of licofelone was observed. In the presence of UDP-glucuronic acid, licofelone is rapidly converted into the corresponding acyl glucuronide, M1. These results are in conflict with data from clinical studies. After administration of licofelone to humans, M1 plasma concentrations were negligibly low, whereas the exposure of the hydroxy-metabolite M2 achieved values of approximately 20% compared with that of the parent drug. Metabolism studies with human hepatocytes and dual-activity assays with microsomes, which allowed the simultaneous monitoring of hydroxylation and glucuronidation reactions, were performed, and the metabolic pathway of licofelone was elucidated. After glucuronidation, predominantly catalyzed by UDP glucuronosyltransferase (UGT) isoforms UGT2B7, UGT1A9, and UGT1A3, M1 is converted into the hydroxy-glucuronide M3 in a CYP2C8-dependent reaction. The enzyme specificities were investigated using recombinant human cytochrome P450 and UGT isoforms as test systems. In vitro drug-interaction studies using the 6α-hydroxylation of paclitaxel as control reaction confirmed that neither licofelone nor M1 is a relevant inhibitor of CYP2C8. The formation of M3 was also observed with liver microsomes from cynomolgus monkeys, but in incubations with mouse and rat liver microsomes, M1 remained unchanged. The clinical relevance of these findings is discussed.
Tumor-selective induction of apoptosis and the small-molecule immune response modifier imiquimod.

BACKGROUND The incidence of nonmelanoma skin cancer, basal cell carcinomas (BCCs), and squamous cell carcinomas (SCCs) is increasing, representing a major medical and economic problem. Imiquimod, a topical small-molecule immune response modifier, has shown efficacy toward BCC and actinic keratoses in clinical trials. Imiquimod acts both indirectly, via cytokine-mediated stimulation of cellular immune responses, and directly, through unknown mechanisms against tumor cells. We examined the mechanism by which imiquimod induces apoptosis in cancer cells. METHODS Apoptosis was assessed by enzyme-linked immunosorbent assay, western blot analysis, and terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) assays in five SCC cell lines, HaCaT cells (a spontaneously immortalized human keratinocyte cell line), and normal keratinocytes treated with imiquimod, with its analog resiquimod, or with neither. Expression of death receptors, caspases, and cytochrome c in the apoptotic signaling cascade was analyzed using western blot and flow cytometric analyses. The functional relevance of imiquimod-induced cytochrome c release was assessed by transfection of HaCaT cells with Bcl-2. Apoptosis in BCCs in vivo was assessed by TUNEL assays of imiquimod-treated and untreated tumors from three patients. Differences between treated and untreated cells and tumors were determined using a two-tailed Student's t test. RESULTS Imiquimod, but not resiquimod, induced apoptosis in all SCC cell lines and HaCaT cells. This induction involved activation of several caspases and Bcl-2-dependent cytosolic translocation of cytochrome c but was independent of the membrane-bound death receptors Fas, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-R1-R4 receptors, and tumor necrosis factor-R1 and -R2 receptors. Topical application of imiquimod to BCC tumors in vivo induced apoptosis. CONCLUSION Imiquimod has the potential to induce apoptosis in skin cancer cells, possibly by circumventing mechanisms developed by malignant tumors to resist apoptotic signals.
Capacity Achieving Pilot Design for MIMO-OFDM over Time-Varying Frequency-Selective Channels

In this paper we analyze the capacity of MIMO-OFDM systems that utilize pilot symbols to acquire estimation of the radio channel at the receiver. An analytical framework is developed to derive the optimal pilot boost and optimal pilot overhead over time-variant frequency selective channels. In addition, to illustrate the achievable capacity, several numerical examples are given assuming different pilot boosts, pilot overheads, and number of transmit antennas.
Genetic and ICP Laser Point Matching for 2 D Mobile Robot Motion Estimation ∗

The paper reports on mobile robot motion estimation based on matching points from successive two-dimensional (2D) laser scans. This ego-motion approach is well suited to unstructured and dynamic environments because it directly uses raw laser points rather than extracted features. We have analyzed the application of two methods that are very different in essence: i) A 2D version of Iterative Closest Point (ICP), which is widely used for surface registration; ii) A Genetic Algorithm (GA), which is a novel approach for this kind of problem. Their performance in terms of real-time applicability and accuracy has been compared in outdoor experiments with non-stop motion under diverse realistic navigation conditions. Based on this analysis, we propose a hybrid GA-ICP algorithm that combines the best characteristics of these pure methods. The experiments have been carried out with the tracked mobile robot Auriga-α and an on-board 2D laser scanner. ∗This research was partially supported by the Spanish CICYT projects DPI 2002-01319 and DPI 2002-04401-C03-01
From One Point to A Manifold: Orbit Models for Knowledge Graph Embedding

Knowledge graph embedding aims at offering a numerical paradigm for knowledge representation by translating the entities and relations into continuous vector space. This paper studies the problem of unsatisfactory precise knowledge embedding and attributes a new issue to this problem that \textbf{\textit{inaccuracy of truth characterization}}, indicating that existing methods could not express the true facts in a fine degree. To alleviate this issue, we propose the orbit-based embedding model, \textbf{OrbitE}. The new model is a well-posed algebraic system that expands the position of golden triples from one point in current models to a manifold. Extensive experiments show that the proposed model achieves substantial improvements against the state-of-the-art baselines, especially for precise prediction.
Automatic relevant Source Discovery over the Internet based on user profile

The enormous growth of the Web in recent years has made difficult the discovery of new sources of interest on a given topic, even thanks to an existing set of relevant sources. To address this problem, we introduce an approach to provide users with new relevant sources of information by exploiting their needs. It aims at combining a personalized crawler with a collaborative filtering system. We study the interest of exploiting the user profile during the crawling process in order to avoid collecting and indexing all available Web documents. We also discuss issues and the development of such a system. MOTS-CLÉS : Modélisation de profil utilisateur, recherche d’information, retour utilisateur, exploration ciblée.