Miracle-dz/UniFAR-FTUs huggingface dataset:
Topology Control in Unreliable Ad hoc Networks : Obtaining Near-Optimal Power Efficiency and Low Interference

Topology control is a basic subroutine in many wireless networking problems and is, in general, a multi-criteria optimization problem involving (contradictory) objectives of connectivity, interference, and power minimization. Wireless devices are often unreliable, and motivated by mission critical networks (which require ensuring reliable system performance), we study topology control problems in ad hoc networks under node failures for arbitrary node distributions. We consider a simple and natural stochastic failure model, in which each node can fail independently with a given probability. The Topology Control Problem Under Stochastic Failures is to choose a power level for each node and a subset of edges such that the residual graph (i.e., the graph formed by the nodes which have not failed) is connected and can be scheduled efficiently, with high probability. We develop provably efficient bi-criteria approximation algorithms for this problem that simultaneously minimize power, reduce interference, and ensure that the surviving graph is connected with high probability. Our algorithms can be implemented efficiently in a distributed manner.
Biological Role of Dystroglycan in Schwann Cell Function and Its Implications in Peripheral Nervous System Diseases

Dystroglycan is a central component of the dystrophin-glycoprotein complex (DGC) that links extracellular matrix with cytoskeleton, expressed in a variety of fetal and adult tissues. Dystroglycan plays diverse roles in development and homeostasis including basement membrane formation, epithelial morphogenesis, membrane stability, cell polarization, and cell migration. In this paper, we will focus on biological role of dystroglycan in Schwann cell function, especially myelination. First, we review the molecular architecture of DGC in Schwann cell abaxonal membrane. Then, we will review the loss-of-function studies using targeted mutagenesis, which have revealed biological functions of each component of DGC in Schwann cells. Based on these findings, roles of dystroglycan in Schwann cell function, in myelination in particular, and its implications in diseases will be discussed in detail. Finally, in view of the fact that understanding the role of dystroglycan in Schwann cells is just beginning, future perspectives will be discussed.
Defining a session on Web search engines

Detecting query reformulations within a session by a Web searcher is an important area of research for designing more helpful searching systems and targeting content to particular users. Methods explored by other researchers include both qualitative (i.e., the use of human judges to manually analyze query patterns on usually small samples) and nondeterministic algorithms, typically using large amounts of training data to predict query modification during sessions. In this article, we explore three alternative methods for detection of session boundaries. All three methods are computationally straightforward and therefore easily implemented for detection of session changes. We examine 2,465,145 interactions from 534,507 users of Dogpile.com on May 6, 2005. We compare session analysis using (a) Internet Protocol address and cookie; (b) Internet Protocol address, cookie, and a temporal limit on intrasession interactions; and (c) Internet Protocol address, cookie, and query reformulation patterns. Overall, our analysis shows that defining sessions by query reformulation along with Internet Protocol address and cookie provides the best measure, resulting in an 82% increase in the count of sessions. Regardless of the method used, the mean session length was fewer than three queries, and the mean session duration was less than 30 min. Searchers most often modified their query by changing query terms (nearly 23% of all query modifications) rather than adding or deleting terms. Implications are that for measuring searching traffic, unique sessions may be a better indicator than the common metric of unique visitors. This research also sheds light on the more complex aspects of Web searching involving query modifications and may lead to advances in searching tools.
Developing Adaptability Developing Adaptability : A Theory for the Design of Integrated-Embedded Training Systems

Author Affiliations: Steve W. J. Kozlowski, Department of Psychology, Michigan State University; Daniel A. Weissbein, Department of Psychology, Michigan State University; Kenneth G. Brown, Department of Management and Organizations, University of Iowa; Rebecca J. Toney, Department of Psychology, Michigan State University; Morell E. Mullins, Department of Psychology, Virginia Polytechnic Institute and State University; Bradford S. Bell, Department of Psychology, Michigan State University.
It is not worth learning if it is not remembered: designing e-learning to increase memory

The collation, storage and retrieval of information are essential components of successful learning. Whether information is retained depends on a variety of factors, including how the information fits with an individual’s existing knowledge, the way in which information is presented, and its complexity. Some of these factors are under the direct control of the e-learning designers and developers. Investigating these factors and how they impact on memory is important and can enhance the quality of e-learning. Evidence from cognitive neuroscience suggests that information is stored in a semantically meaningful manner. It follows that e-learning technologies, which either mimic how knowledge is structured in the mind or which allow individuals to organise their own exploration of the information space, should facilitate learning and memory. However, the ability to freely explore an information space is also more taxing on an individual’s cognitive resources. Learners would need to expend cognitive resources remembering where they have been, as well as on deciding where to go next. These additional demands may impede learning, especially for more complex information. Most critical to investigate is the trade-off between the ability to build knowledge according to the learners’ cognitive structures and style (which is also more engaging), on the one hand; and the extra cognitive load associated with giving learners more control and information, on the other hand. In this study we investigated the relationship between information layout, complexity of information content, and memory. Seventy-six participants took part in the study. A third of them were presented with information that was laid out in a linear fashion: learners encountered the items of information in a fixed and constrained sequence. This layout provided a structure for remembering the presented information and minimised cognitive load. Another third of the participants were given full control; they could select the order in which they learned the different topics and could freely navigate between them. This layout increased cognitive load and eliminated context structure, but was also potentially more engaging and allowed for individual differences. The remaining third of participants received an intermediate version, giving some, but not total, control. All the participants studied eight topics, half of them were given relatively simple information on each topic, whereas the other half where given more complex information. The acquisition and retention of the learned material was assessed in all the experimental conditions. We found that constraining both the amount of information presented to the learners and the degree of navigational freedom they are given enhances information acquisition and retention. These factors are further discussed in terms of Cognitive Load Theory (CLT). Finally, the implication and application to e-learning design is considered.
Local News Chatter: Augmenting Community News by Aggregating Hyperlocal Microblog Content in a Tag Cloud

Being aware of local community information is critical to maintaining civic engagement and participation. The use of online news and microblog content to create and disseminate community information has long been studied. However, interactions in the online spaces dedicated to local communities tend to only garner very limited usage, and people often do not consider microblog content as a meaningful source of local community information. Local News Chatter (LNC) was designed to address these challenges by augmenting local news feeds with microblog content and presenting them in a tag cloud that displays news topics of varying popularity with different tag sizes. Our study with 30 local residents highlights that LNC increases the visibility of hyperlocal community news information and successfully utilizes microblog as an additional information layer. LNC also increases one’s community awareness and shows the potential for leveraging community knowledge as a deliberation platform for local topics.
Self-Regulated Music Practice: Microanalysis as a Data Collection Technique and Inspiration for Pedagogical Intervention

The purpose of this study was to explore a microanalysis technique for measuring instrumentalists’ self-regulation tendencies during music practice. A secondary purpose was to investigate whether an intervention informed by the features of the microanalysis technique would increase the students’ self-regulated learning tendencies. Three undergraduate instrumental music education majors volunteered to participate in this study. This study was designed as a multiple-baselines experiment spanning 15 consecutive days. Data sources included (a) entrance interviews; (b) daily practice efficacy ratings; (c) data gathered from pre- and posttest microanalysis sessions; (d) detailed behavioral analyses of video-recorded, pre- and posttest practice sessions; and (e) a focus group exit interview. The microanalytic intervention designed for this study involved a coaching session in which a member of the research team explicitly drew attention to the affective, behavioral, and metacognitive qualities related to effective practicing during a student’s practice session. The pretest microanalysis data revealed distinct learning profiles for each student that were corroborated with information from the other data sources. The intervention had modest effects that varied across participants, suggesting that it was useful for bringing to light and addressing individuals’ specific self-regulatory deficiencies in a manner respective to their needs.
Developing Advanced Tools for Processing Hyperspectral Images

In many applications, according to [15], a fundamental processing task is to automatically identify pixels whose spectra coincide with the given spectral shape (signature). This problem raises the following issues: How the measured spectrum of a ground material is related to a given “pure” spectrum and how to compare between them to determine if they are the same? Spatial and spectral sampling produce a 3D data structure referred to as a data cube. Figure 1.1, taken from [15], shows an example of an hyper-spectral data cube.
Random Regular Graphs: Asymptotic Distributions and Contiguity

The asymptotic distribution of the number of Hamilton cycles in a random regular graph is determined. The limit distribution is of an unusual type; it is the distribution of a variable whose logarithm can be written as an infinite linear combination of independent Poisson variables, and thus the logarithm has an infinitely divisible distribution with a certain discrete Lévy measure. Similar results are found for some related problems. These limit results imply that some different models of random regular graphs are contiguous, which means that they are qualitatively asymptotically equivalent. For example, if r > 3, then the usual (uniformly distributed) random r-regular graph is contiguous to the one constructed by taking the union of r perfect matchings on the same vertex set (assumed to be of even cardinality), conditioned on there being no multiple edges. Some consequences of contiguity for asymptotic distributions are discussed.
Role Playing in Storytelling Classes and Its Impact on Iranian Young EFL Learners’ Narrative Writing

The present study aimed to investigate the effect of role playing in storytelling classes on Iranian young EFL learners’ narrative writing. Forty-seven pre-intermediate young EFL learners who were within the age range of 9 and 16 participated in this study. They were members of four intact classes, which consisted of two classes of boys and two classes of girls. One class of boys and one class of girls were randomly assigned to the experimental groups and the other two to control groups. The researchers used the role-playing technique for storytelling classes in the experimental groups and only reading stories aloud for storytelling classes in the control groups. After the treatment, the Multivariate Analysis of Variance (MANOVA) was run to compare the four groups’ improvement on narrative writing. The results signified that the use of role playing in the storytelling classes had a significant impact on the narrative writing of Iranian young EFL learners as compared to the reading stories aloud technique. Furthermore, the findings showed that using role playing in storytelling classes enhanced learners’ understanding of the narrative writing style and patterns of the target language.
Computational prediction of the localization of microRNAs within their pre-miRNA

MicroRNAs (miRNAs) are short RNA species derived from hairpin-forming miRNA precursors (pre-miRNA) and acting as key posttranscriptional regulators. Most computational tools labeled as miRNA predictors are in fact pre-miRNA predictors and provide no information about the putative miRNA location within the pre-miRNA. Sequence and structural features that determine the location of the miRNA, and the extent to which these properties vary from species to species, are poorly understood. We have developed miRdup, a computational predictor for the identification of the most likely miRNA location within a given pre-miRNA or the validation of a candidate miRNA. MiRdup is based on a random forest classifier trained with experimentally validated miRNAs from miRbase, with features that characterize the miRNA–miRNA* duplex. Because we observed that miRNAs have sequence and structural properties that differ between species, mostly in terms of duplex stability, we trained various clade-specific miRdup models and obtained increased accuracy. MiRdup self-trains on the most recent version of miRbase and is easy to use. Combined with existing pre-miRNA predictors, it will be valuable for both de novo mapping of miRNAs and filtering of large sets of candidate miRNAs obtained from transcriptome sequencing projects. MiRdup is open source under the GPLv3 and available at http://www.cs. mcgill.ca/∼blanchem/mirdup/.
Scaling of neuron number and volume of the pulvinar complex in new world primates: Comparisons with humans, other primates, and mammals

The lateral posterior nucleus and pulvinar (LP‐pulvinar complex) are the principal thalamic nuclei associated with the elaborate development of the dorsal and ventral streams of the parietal cortex in primates. In humans, a novel site of origin for a subpopulation of pulvinar neurons has been observed, the ganglionic eminence of the telencephalon. This additional site of neuron origin has been proposed to contribute to the pulvinar's evolutionary expansion (Letinic and Rakic [ 2001 ] Nat Neurosci 4:930–936). Studies of neuron number in the LP‐pulvinar complex in gibbon, chimpanzee, and gorilla compared to humans, however, did not show that the human LP‐pulvinar was unexpectedly large (Armstrong [ 1981 ] Am J Phys Anthropol 55:369–383). Here we enlarge the allometric basis for comparison by determining neuron number in the LP‐pulvinar complex of six New World primates (Cebus apella, Saimiri ustius, Saguinus midas niger, Alouatta caraya, Aotus azarae, and Callicebus moloch) as well as measuring LP‐pulvinar volume in a further set of 24 species including additional primates, carnivores, and rodents. The volume of the LP‐pulvinar complex scaled with positive allometry with respect to brain volume across all species examined. The scaling of the number of neurons in the LP‐pulvinar complex was extremely similar in New World primates and anthropoid apes, with the human LP‐pulvinar value close to the regression line. Comparison of the relative volumes of the LP‐pulvinar in the larger sample confirmed this observation, and further demonstrated that both primates and carnivores showed a “grade shift” in its size compared to rodents, with the pulvinar comprising a greater proportion of total brain volume across the board. Diurnal, nocturnal, or crepuscular niche did not discriminate LP‐pulvinar size across taxa. J. Comp. Neurol. 504:265–274, 2007. © 2007 Wiley‐Liss, Inc.
SAT-based analysis of feature models is easy

Feature models are a popular variability modeling notation used in product line engineering. Automated analyses of feature models, such as consistency checking and interactive or offline product selection, often rely on translating models to propositional logic and using satisfiability (SAT) solvers. Efficiency of individual satisfiability-based analyses has been reported previously. We generalize and quantify these studies with a series of independent experiments. We show that previously reported efficiency is not incidental. Unlike with the general SAT instances, which fall into easy and hard classes, the instances induced by feature modeling are easy throughout the spectrum of realistic models. In particular, the phenomenon of phase transition is not observed for realistic feature models. Our main practical conclusion is a general encouragement for researchers to continued development of SAT-based methods to further exploit this efficiency in future.
Do Market Leaders Lead in Business Process Innovation? The Case(s) of E-Business Adoption

Are market leaders more likely to be early adopters of business process innovations? Although they tend to enjoy economies of scale in adoption, leaders may find that adjustment costs also increase with scale. Prior work has focused on how misalignment of incumbents' internal capabilities may affect their technology strategy. However, technology-capability misalignment may exist outside the firm boundary as well. In this paper, I build on mainstream product innovation concepts to predict when market leaders will adopt certain business process innovations. I then test these predictions in a large data set on early e-business adoption, leveraging its novel insight into focal firms, their markets, and their customers. I find market leaders were significantly more likely to embrace new information technology-enabled practices-except when customer adjustment costs were a significant concern. These findings highlight the strategic significance of external capabilities in the face of technological change. This paper was accepted by Bruno Cassiman, business strategy.
On node and route choice models for high-dimensional road networks

This paper discusses first order node models for macroscopic multi-commodity traffic simulation. There are two parts: (1) input-output flow computation based on input demand, input link priorities, split ratios that define how incoming flow is distributed between output links, and output supply; and (2) a traffic assignment algorithm for the case when split ratios are not known a priori or are only partially known. Input link priorities define how output supply is distributed between incoming flows. We deal with arbitrary input link priorities. Also, in this node model we specifically address the issue of the First-In-First-Out (FIFO) rule: in the case of one of the output links being overly congested the FIFO rule may be too restrictive, blocking the flow to other outputs and causing unreasonable spillback. We relax the FIFO rule through a parametrization that describes how output links influence each other and allows tuning the model to anything between full FIFO and no FIFO. In the existing research the prevailing approach to local traffic assignment is to use a mode choice (logit or probit) model. In this paper we discuss the shortcomings of the logit model and introduce a nonparametric route choice algorithm that produces split ratios based only on link demands and supplies. All methods in this paper are presented for multi-commodity traffic flows.
Service Elements Valuation Using an Enterprise Architecture Language

This article defines a service as an architecture of processes, software and infrastructure elements for serving people. An architecture language therefore is a means to structure and analyze the values of service elements and the service as a whole. We provide a value-based perspective, which first includes a review of the concept of value in the context of service architectures for services. Here we conclude that multiple, even competing, values are at stake for different parts of a service. Second, the paper discusses a method for the valuation of a service using competing value constructs. We also demonstrate by a case how a formal architecture language can be used to calculate service values. Finally, the results are discussed and suggestions for further research are given
Educator Sexual Misconduct: A Statutory Analysis

Educator sexual misconduct is a problem that has gained increased attention because of the high-profile cases reported by the news media. Yet, the diversity in state law regarding this offense remains somewhat unexplored. In this article, we compare and evaluate state statutory provisions regarding educator sexual misconduct; our focus is on what constitutes educator sexual misconduct, and what penalties are provided for offenders. As such, we explore the differences and similarities in statutory provisions across states in terms of the definition of child sexual assault, the age of consent, the penalties for various types of sexual misconduct perpetrated by teachers, and any requirement for registration as sex offenders. Our findings indicate that though the number of applicable statutes has almost doubled since 2010, there remains a wide variety in the definition and penalties included in those laws, and 21 states have not chosen to enact a specific law at all.
ANÁLISIS DE LA RELACIÓN ENTRE DEPRESIÓN Y ESTILO DE VIDA EN ADOLESCENTES

El objetivo del estudio fue analizar la relacion entre depresion y estilo de vida (EV). Participaron 523 adolescentes. Se evaluo la depresion mediante el Children’s Depression Inventory -CDI- (Del Barrio y Carrasco, 2004), el estilo de vida (EV) con una escala tipo Likert disenada ad hoc con 6 dimensiones: 1. Alimentacion, 2. Actividad fisica, 3. Estado emocional, 4. Relaciones sociales, 5. Toxicomanias y 6. Salud, tambien se exploraron las variables genero y grado escolar. Los resultados muestran que no existen correlaciones significativas entre los puntajes totales de depresion y estilo de vida (EV), sin embargo entre las subescalas humor negativo con alimentacion, relaciones sociales y el total de EV se observa una correlacion media significativa (r=0.62, r=0.75 y r=0.69; p<0.05); tambien se observo que conforme el grado academico avanza, los chicos muestran mas problemas interpersonales, problemas de autoestima y anhedonia algo similar sucede con el EV, el genero no mostro diferencias significativas en ninguna de las dos escalas. Se concluye que la adolescencia es una etapa desafiante para los adolescentes, sus padres y los profesionales de la salud, pues debe intervenirse ante la presencia de sintomas depresivos, ya que estos guardan relacion con el EV.