Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure and Efficient Data Transmission for Cluster Based Wireless Sensor Networks C

Wireless Sensor Networks (WSN) plays vital role in research field. Due to its rapidly increasing application in monitoring various kinds of environment by sensing physical phenomenon. Clustering is an efficient and effective method to enhance performance of the WSNs system. In this project work, we study a secure transmission of data for clusterbased WSNs (CWSNs), where the clusters are formed dynamically and randomly. We propose two Secure and Efficient data Transmission (SET) protocols for CWSNs, called SET-IBS and SET-IBOOS, by using the IdentityBased digital Signature (IBS) scheme and the Identity-Based Online/Offline digital Signature (IBOOS) scheme, respectively. The cluster routing protocol LEACH (LowEnergy Adaptive Clustering Hierarchy) is considered and improved. In SET-IBS, security relies on the hardness of the Diffie-Hellman problem in the pairing area. SET-IBOOS additionally decreases the computational operating cost for protocol security, which is critical for WSNs, while its defense depends on the stability of the problem of discrete logarithm. We propose a clustering routing protocol named Enhanced LEACH, which extends LEACH protocol by balancing the energy consumption in the network. The simulation results show that Enhanced LEACH outperforms LEACH in terms of network system lifetime and reduce the
BOTULINUM TOXIN FOR DIABETIC NEUROPATHIC PAIN: A RANDOMIZED DOUBLE-BLIND CROSSOVER TRIAL

We are skeptical of the benefits of botulinum toxin type A (BoNT/A) in treating neuropathic pain.1 We also believe that Apfel's2 accompanying editorial was too positive regarding this study involving only 18 patients. Sleep problems and quality of life scores have nothing in common with results of the visual analog scale (VAS) and these are our patients' major concerns. In addition, the pattern of injections is not related to the areas where our patients complain about pain, including the toes and balls of the feet. Furthermore, data have shown that injection sites followed the pain.3,4 The study would have benefited by having independent funding rather than relying on the largess of Allergan for the BoNT/A. BoNT/A has proven indications, but the drive to expand them is industry-driven and is reminiscent of the marketing strategy of …
3D rotation invariant local binary patterns

We present a novel method for the fast computation of rotation invariant ¿local binary patterns¿ (LBP) on 3D volume data. Unlike a previous publication on 3D LBP, this new approach is not limited to ¿uniform patterns¿, providing a real 3D extension of the standard and rotation invariant LBP. We evaluate our methods in the context of 3D texture analysis of biological data.
Protein Structure Validation and Identification from Unassigned Residual Dipolar Coupling Data Using 2D-PDPA

More than 90% of protein structures submitted to the PDB each year are homologous to some previously characterized protein structure. The extensive resources that are required for structural characterization of proteins can be justified for the 10% of the novel structures, but not for the remaining 90%. This report presents the 2D-PDPA method, which utilizes unassigned residual dipolar coupling in order to address the economics of structure determination of routine proteins by reducing the data acquisition and processing time. 2D-PDPA has been demonstrated to successfully identify the correct structure of an array of proteins that range from 46 to 445 residues in size from a library of 619 decoy structures by using unassigned simulated RDC data. When using experimental data, 2D-PDPA successfully identified the correct NMR structures from the same library of decoy structures. In addition, the most homologous X-ray structure was also identified as the second best structural candidate. Finally, success of 2D-PDPA in identifying and evaluating the most appropriate structure from a set of computationally predicted structures in the case of a previously uncharacterized protein Pf2048.1 has been demonstrated. This protein exhibits less than 20% sequence identity to any protein with known structure and therefore presents a compelling and practical application of our proposed work.
Binding of b-Amyloid to the p 75 Neurotrophin Receptor Induces Apoptosis A Possible Mechanism for Alzheimer ’ s Disease

Alzheimer’s disease is a neurodegenerative disorder characterized by the extracellular deposition in the brain of aggregated b -amyloid peptide, presumed to play a pathogenic role, and by preferential loss of neurons that express the 75-kD neurotrophin receptor (p75 NTR ). Using rat cortical neurons and NIH-3T3 cell line engineered to stably express p75 NTR , we find that the b -amyloid peptide specifically binds the p75 NTR . Furthermore, 3T3 cells expressing p75 NTR , but not wild-type control cells lacking the receptor, undergo apoptosis in the presence of aggregated b -amyloid. Normal neural crest–derived melanocytes that express physiologic levels of p75 NTR undergo apoptosis in the presence of aggregated b -amyloid, but not in the presence of control peptide synthesized in reverse. These data imply that neuronal death in Alzheimer’s disease is mediated, at least in part, by the interaction of b -amyloid with p75 NTR , and suggest new targets for therapeutic intervention. ( J. Clin. Invest. 1997. 100:2333–2340.)
Gaming at the Edge: Sexuality and Gender at the Margins of Gamer Culture

Video games have long been seen as the exclusive territory of young, heterosexual white males. In a media landscape dominated by such gamers, players who do not fit this mold, including women, people of color, and LGBT people, are often brutalized in forums and in public channels in online play. Discussion of representation of such groups in games has frequently been limited and cursory. In contrast, Gaming at the Edge builds on feminist, queer, and postcolonial theories of identity and draws on qualitative audience research methods to make sense of how representation comes to matter. In Gaming at the Edge, Adrienne Shaw argues that video game players experience race, gender, and sexuality concurrently. She asks: How do players identify with characters? How do they separate identification and interactivity? What is the role of fantasy in representation? What is the importance of understanding market logic? In addressing these questions Shaw reveals how representation comes to matter to participants and offers a perceptive consideration of the high stakes in politics of representation debates. Putting forth a framework for talking about representation, difference, and diversity in an era in which user-generated content, individualized media consumption, and the blurring of producer/consumer roles has lessened the utility of traditional models of media representation analysis, Shaw finds new insight on the edge of media consumption with the invisible, marginalized gamers who are surprising in both their numbers and their influence in mainstream gamer culture.
POS tagset design for Italian

We aim to automatically induce a PoS tagset for Italian by analysing the distributional behaviour of Italian words. To this end, we propose an algorithm that (a) extracts information from loosely labelled dependency structures that encode only basic and broadly accepted syntactic relations, namely Head/Dependent and the distinction of dependents into Argument vs. Adjunct, and (b) derives a possible set of word classes. The paper reports on some preliminary experiments carried out using the induced tagset in conjunction with state-of-the-art PoS taggers. The method proposed to design a proper tagset exploits little, if any, language-specific knowledge: hence it is in principle applicable to any language.
Multiplex 5′ Nuclease Quantitative Real-Time PCR for Clinical Diagnosis of Malaria and Species-Level Identification and Epidemiologic Evaluation of Malaria-Causing Parasites, Including Plasmodium knowlesi

ABSTRACT Molecular diagnosis of malaria offers many potential advantages over microscopy, including identification of malaria to the species level in an era with few experienced microscopists. We developed high-throughput multiplex 5′ nuclease quantitative PCR (qPCR) assays, with the potential to support large studies, to specifically identify Plasmodium falciparum, P. vivax, P. ovale, P. malariae, and P. knowlesi. We compared qPCR to microscopy and confirmed discordant results with an alternative target PCR assay. The assays specifically detected 1 to 6 parasites/μl of blood. The clinical sensitivities (95% confidence intervals [CIs]) of the 4-plex assay to detect microscopically confirmed malaria were 95.8% (88.3 to 99.1%) for P. falciparum, 89.5% (75.2 to 97.1%) for P. vivax, 94.1% (71.3 to 99.9%) for P. ovale, and 100% (66.4 to 100%) for P. malariae. The specificities (95% CIs) were 98.6% (92.4 to 100%) for P. falciparum, 99% (84.8 to 100%) for P. vivax, 98.4% (94.4 to 99.8%) for P. ovale, and 99.3% (95.9 to 100%) for P. malariae. The clinical specificity for samples without malaria was 100%. The clinical sensitivity of the 5-plex assay for confirmed P. knowlesi malaria was 100% (95% CI, 69.2 to 100%), and the clinical specificity was 100% (95% CI, 87.2 to 100%). Coded retesting and testing with an alternative target PCR assay showed improved sensitivity and specificity of multiplex qPCR versus microscopy. Additionally, 91.7% (11/12) of the samples with uncertain species by microscopy were identified to the species level identically by both our multiplex qPCR assay and the alternative target PCR assay, including 9 P. falciparum infections. Multiplex qPCR can rapidly and simultaneously identify all 5 Plasmodium species known to cause malaria in humans, and it offers an alternative or adjunct to microscopy for clinical diagnosis as well as a needed high-throughput tool for research.
The Sage handbook of interpersonal communication

PART I: Basic Issues and Approaches 1. Background and Current Trends in the Study of Interpersonal Communication - Mark L. Knapp & John A. Daly PART II: Perspectives on Inquiry 2. Quantitative Social Science Methods of Inquiry - Tim Levine 3. Qualitative Methods in Interpersonal Communication - Karen Tracy & Christine Fitch 4. Biological and Physiological Perspectives on Interpersonal Communication - Kory Floyd & Tammy Afifi PART III: Fundamental Units 5. Personality and Interpersonal Communication - John A. Daly 6. Knowledge Structures and Social Interaction - Charles R. Berger & Nicholas A. Palomares 7. Language and Interpersonal Communication - Matthew S. McGlone & Howard Giles 8. Nonverbal Signals - Judee K. Burgoon, Laura K. Guerrero, & Valerie Manusov PART IV: Processes and Functions 9. Emotion Experience and Expression: Current Trends and Future Directions in Interpersonal Relationship Research - Sandra Metts & Sally Planalp 10. Supportive Communication - E.L. MacGeorge, B. Feng, and B. R. Burleson 11. Social Networks and the Life of Relationships - Malcolm R. Parks 12. Interpersonal Influence - James P. Dillard & Leanne Knobloch 13. Interpersonal Conflict: A Review - Michael E. Roloff & Benjamin Chiles 14. Theories of Computer Mediated Communication and Interpersonal Relations - Joseph B. Walther 15. Interpersonal Skills - Brian H. Spitzberg & William R. Cupach PART V: Contexts 16. Interpersonal Communication in the Workplace - Karen K. Myers, David R. Seibold, & Hee Sun Park 17. Intercultural Perspectives on Interpersonal Communication - John Oetzel & Stella Ting-Toomey 18. Interpersonal Processes in Romantic Relationships - Anita L. Vangelisti 19. Interpersonal Communication and Health Care - Teresa L. Thompson, Jeffrey D. Robinson, & Dale E. Brashers 20. Interpersonal Communication in Family Relationships - John P. Caughlin, Ascan F. Koener, Paul Schrodt, & Mary Anne Fitzpatrick 21. Interpersonal Communication Across the Lifespan - Jon F. Nussbaum, Loretta L. Pechionni, & Kevin B. Wright Author Index Subject Index About the Authors
GAPK: Genetic algorithms with prior knowledge for motif discovery in DNA sequences

Discovery of transcription factor binding sites (TFBSs) or DNA motifs in promoter regions of genes plays a key role in understanding the regulations of gene expression. In the past decade computational approaches, including evolutionary computation techniques, for searching for motifs have demonstrated good potential, and some results reported in literature are quite promising. Recently, some favorable progresses on evolutionary mining of motifs have been made and documented in GAME and GALF-P, where GAME employs a Bayesian-based scoring function and GALF-P aims to improve the algorithm performance with local filtering and adaptive post-processing. To improve discovering performance in terms of the recall, precision rates and algorithm reliability, this paper presents an alternative genetic algorithm termed as GAPK for resolving the problem of motifs discovery. In our proposed GAPK framework, a prior knowledge on motifs in a given dataset is used to initialize a population. Our technical contributions include a matrix representation for k-mers, a mismatch-based filtering method for search space reduction, a model mismatch score (MMS) as fitness function, new genetic operations and a model refinement processing. Some benchmarked datasets associated with eight transcription factors are used in our experiments. Comparative studies were carried out with well-known tools including GAME, GALF-P, MEME, MDScan and AlignACE. Results show that our method outperforms other techniques in terms of F-measure.
Secure access control for multi-cloud resources

Privacy, security, and trust concerns are continuously hindering the growth of cloud computing despite its attractive features. To mitigate these concerns, an emerging approach targets the use of multi-cloud architectures to achieve portability and reduce cost. Multi-cloud architectures however suffer several challenges including inadequate cross-provider APIs, insufficient support from cloud service providers, and especially non-unified access control mechanisms. Consequently, the available multi-cloud proposals are unhandy or insecure. This paper proposes two contributions. At first, we survey existing cloud storage provider interfaces. Following, we propose a novel technique that deals with the challenges of connecting modern authentication standards and multiple cloud authorization methods.
Adicción a Internet: revisión crítica de la literatura

Introduction: Internet Addiction (IA) is a psychological dependence. Symptoms of IA often include increased preoccupation with online activities, symptoms of withdrawal when not online, tolerance and denial of IA. Objective: The objective of this paper is to make a critical, in depth and update review of the scientifi c literature about IA. Results- conclusion: IA’s importance in public health lies in the ongoing increase of its prevalence around the world especially in adolescents, with serious consequences on their mental health such as family problems, impaired social relations and academic achievement, alcohol, cigarette and other substance abuse and the presence of mental disorders such as depression, bipolar disorder, ADHD (Attention Defi cit Hyperactivity Disorder) and suicidal behavior. Even though Colombian society and the media have shed a light upon its presence and consequences, there are not any studies about the prevalence of Internet Addiction in Colombia and its associated risk factors, explained in part by the absence of a psychometrically developed assessment instrument.
Super Resolution TOA Estimation Algorithm with Maximum Likelihood ICA Based Pre-Processing

High-resolution time of arrival (TOA) estimation techniques have great promise for the high range resolution required in recently developed radar systems. A widely known super-resolution TOA estimation algorithm for such applications, the multiple-signal classification (MUSIC) in the frequency domain, has been proposed, which exploits an orthogonal relationship between signal and noise eigenvectors obtained by the correlation matrix of the observed transfer function. However, this method suffers severely from a degraded resolution when a number of highly correlated interference signals are mixed in the same range gate. As a solution for this problem, this paper proposes a novel TOA estimation algorithm by introducing a maximum likelihood independent component analysis (MLICA) approach, in which multiple complex sinusoidal signals are efficiently separated by the likelihood criteria determined by the probability density function (PDF) of a complex sinusoid. This MLICA schemes can decompose highly correlated interference signals, and the proposed method then incorporates the MLICA into the MUSIC method, to enhance the range resolution in richly interfered situations. The results from numerical simulations and experimental investigation demonstrate that our proposed pre-processing method can enhance TOA estimation resolution compared with that obtained by the original MUSIC, particularly for lower signal-to-noise ratios. key words: maximum likelihood independent component analysis (MLICA), multiple signal classification (MUSIC), super-resolution TOA estimation, highly correlated signal separation
Extended balanced truncation for parameter-varying multidimensional systems

In this work, a novel technique of balanced truncation for model reduction of parameter-varying multidimensional systems in “Roesser Form” is proposed. The multidimensional system representation requires two operators defined on l2-space. The reduction is based on extended Gramians. Both, standard and improved error bounds for the model reduction problem are presented. The approach is demonstrated with the application to an illustrative example.
Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification

We consider feature selection and weighting for nearest neighbor classifiers. A technical challenge in this scenario is how to cope with discrete update of nearest neighbors when the feature space metric is changed during the learning process. This issue, called the target neighbor change, was not properly addressed in the existing feature weighting and metric learning literature. In this paper, we propose a novel feature weighting algorithm that can exactly and efficiently keep track of the correct target neighbors via sequential quadratic programming. To the best of our knowledge, this is the first algorithm that guarantees the consistency between target neighbors and the feature space metric. We further show that the proposed algorithm can be naturally combined with regularization path tracking, allowing computationally efficient selection of the regularization parameter. We demonstrate the effectiveness of the proposed algorithm through experiments.
Differential effects of N-linked glycosylation of Vstm5 at multiple sites on surface expression and filopodia formation

V-set and transmembrane domain-containing protein 5 (Vstm5), a newly characterized small membrane glycoprotein, can induce membrane protrusions in various cells. Vstm5 can modulate both the position and complexity of central neurons by altering their membrane morphology and dynamics. In this study, we investigated the significance of glycosylation in the expression and function of Vstm5. Four N-linked glycosylation sites (Asn43, Asn87, Asn101, and Asn108) are predicted to be located in the extracellular N-terminus of mouse Vstm5. Although all four sites were glycosylated, their functional roles may not be identical. N-glycosylation at multiple sites affects differentially the function of Vstm5. Glycosylation at individual sites not only played essential roles in surface expression of Vstm5 but also in the formation of neuronal dendritic filopodia. These results indicate that N-linked glycosylation at multiple sites plays important roles by differentially influencing the expression, targeting, and biological activity of Vstm5.
As construções linguísticas "para" e "para dentro de” e a simulação mental de espaço e movimento

Neste artigo, verificamos em que medida a simulacao mental pode capturar sutilezas da linguagem ao conectar conhecimentos linguisticos a experiencias sensorio-motoras. Em linhas gerais, os resultados demonstram que a simulacao se torna mais detalhada em funcao de pistas linguisticas fornecidas pelos enunciados e pelos padroes linguisticos analisados em termos de construcoes gramaticais; e pelas especificacoes semânticas resolvidas no contexto comunicativo em curso durante a leitura/ audicao de enunciados. Neste estudo, analisamos como as construcoes prepositivas “para” e “para dentro de” contribuem para a construcao do sentido de espaco e movimento. Para isso, recorremos a uma abordagem corporificada de gramatica de construcao, que nos permitiu identificar os tipos de imagens mentais construidas durante a analise de construcoes linguisticas de espaco e movimento e como os componentes dos esquemas acionados se integram durante o processo de simulacao mental.
Asymmetric Explanations of Group Differences: Experimental Evidence of Foucault’s Disciplinary Power

Whilst the same group differences can be explained in many ways, explanations of group differences tend to spontaneously figure the distinctive attributes of lower-status groups against a background norm of high-status groups’ attributes. We suggest that this asymmetry occurs in the explanations of scientists and laypeople who have been influenced by the history of ‘disciplinary power’ which works to disempower lower-status people by making them visible to the human sciences. We argue that social groups who are habitually studied first in research programs, more commonly encountered social groups, and prototypical social groups are all less likely than their counterparts to be marked in spontaneous explanations of empirical group differences. We present evidence that groups who are explicitly mentioned in such explanations are assumed to be lower in power. We describe some limitations to current knowledge about such asymmetric explanations and suggest some directions for further research, including our thoughts about how to integrate existing findings with the possibility of formulating cognitive alternatives to the status quo among minority groups.
A Different Vision in eLearning: Metaphors.

Metaphors are figures of speech in which a word or phrase that denotes a certain object or idea is applied to another word or phrase to imply some similarity between them. Due to their ability to make speaking and writing more lively and interesting, metaphors have always been popular among students. While metaphors provide significant enhancement of contexts and build upon the sense of community, they can limit the boundaries of the communication between students and teachers. In order to carry out student oriented courses, teachers ought to consider the metaphors students use. In an effort to understand and fill in this communication gap, the authors of this paper have initiated a study that aimed to drive out the e-education students" metaphors in order to suggest a vision for future e-courses. The authors have designed the "E-Education Metaphor Analysis Survey" that comprised 35 items and captured data about e-education students" metaphors. The questionnaire was posted on Surveymonkey.com and was distributed to e-education students in two countries: Turkey and Cyprus. 352 students filled the questionnaire. The answers revealed that the metaphors students use are influenced by their way of life, their personal characteristics, their educational background and their feelings. Internet was the most common metaphor used for e-education. A very interesting fact was that 47% of the students considered E-Student to be equivalent to "rich students" education" and that the term recalled them the metaphor "richness". Although there were many research studies on common metaphors and their impact on e- education, there were no studies in the literature about eLearning metaphors. This paper presents an innovative approach that focuses on 7 key research questions and represents a first step of a more detailed future project undertaken by the authors.