Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating Affymetrix microarray data sets using probe-level test statistic for predicting prostate cancer

Microarray technology has previously been used to identify differentially expressed genes between tumor and normal prostate samples in a single study as well as in a synthesis involving multiple studies. When integrating results from several Affymetrix microarray datasets, previous studies have used probeset-level data which may lead to a loss of information contained at the probe-level. Here, we propose a new approach for combining results across studies, based on a probe-level test statistic. Each probe-level test statistic is transformed into an effect size measure for each probeset and a random-effects model (REM) is used to integrate effect sizes across studies. We compared statistical and biological significance of the prognostic gene expression signatures identified in the probe-level model (PLM) with those in the probeset-level model (PSLM). Support vector machines (SVMs)-based predictive models were built using these two sets of signatures and their performances were evaluated using independent test datasets. Our analyses show that the prognostic gene expression signatures identified through the probe-level test statistics are more strongly differentially expressed and have better prediction accuracy than signatures derived from a probeset-level model
Potential Roles of Exosomal MicroRNAs as Diagnostic Biomarkers and Therapeutic Application in Alzheimer's Disease

Exosomes are bilipid layer-enclosed vesicles derived from endosomes and are released from neural cells. They contain a diversity of proteins, mRNAs, and microRNAs (miRNAs) that are delivered to neighboring cells and/or are transported to distant sites. miRNAs released from exosomes appear to be associated with multiple neurodegenerative conditions linking to Alzheimer's disease (AD) which is marked by hyperphosphorylated tau proteins and accumulation of Aβ plaques. Exciting findings reveal that miRNAs released from exosomes modulate the expression and function of amyloid precursor proteins (APP) and tau proteins. These open up the possibility that dysfunctional exosomal miRNAs may influence AD progression. In addition, it has been confirmed that the interaction between miRNAs released by exosomes and Toll-like receptors (TLR) initiates inflammation. In exosome support-deprived neurons, exosomal miRNAs may regulate neuroplasticity to relieve neurological damage. In this review, we summarize the literature on the function of exosomal miRNAs in AD pathology, the potential of these miRNAs as diagnostic biomarkers in AD, and the use of exosomes in the delivery of miRNAs which may lead to major advances in the field of macromolecular drug delivery.
Optimal Selection of Preemption Points to Minimize Preemption Overhead

A central issue for verifying the schedulability of hard real-time systems is the correct evaluation of task execution times. These values are significantly influenced by the preemption overhead, which mainly includes the cache related delays and the context switch times introduced by each preemption. Since such an overhead significantly depends on the particular point in the code where preemption takes place, this paper proposes a method for placing suitable preemption points in each task in order to maximize the chances of finding a schedulable solution. In a previous work, we presented a method for the optimal selection of preemption points under the restrictive assumption of a fixed preemption cost, identical for each preemption point. In this paper, we remove such an assumption, exploring a more realistic and complex scenario where the preemption cost varies throughout the task code. Instead of modeling the problem with an integer programming formulation, with exponential worst-case complexity, we derive an optimal algorithm that has a linear time and space complexity. This somewhat surprising result allows selecting the best preemption points even in complex scenarios with a large number of potential preemption locations. Experimental results are also presented to show the effectiveness of the proposed approach in increasing the system schedulability.
Official Frames and Corporate Environmental Pollution

This paper examines a contentious environmental dispute surrounding a decommissioned zinc smelter facility in Blackwell, Oklahoma. The environmental conflict stems from potential health effects associated with lead, cadmium, and arsenic contamination. The company that owns the former zinc smelter facility argues that they are in compliance with all environmental health and safety standards and city residents praise their ongoing remediation efforts. Based on in-depth interviews, observation, and thematic content analysis, we examine the company's establishment of an official frame to characterize their role in the environmental case. This frame is based on corporate citizenship, the diffusion of responsibility, and the multiplicity of contamination sources. We examine the salience of this frame within the broader community and address challenges to the official frame by local community activists. The results of the study indicate that local community residents are at a tremendous disadvantage when challenging large corporate polluters.
Applying Machine Learning Techniques to a Real Cognitive Network: File Transfer ETAs Prediction

Cognitive Network (CN) paradigm and Machine Learning (ML) techniques are increasingly becoming popular in Wireless network design. CN allows to efficiently arrange the network stack parameters among the nodes involved in the data transmission. It can be divided into two modules: the former permits to retrieve the ISO/OSI protocol stack parameters and the latter optimizes the transmission through a Cognitive Engine entity. This engine usually adopts ML algorithms to extract important features regarding the network, with the objective of either maximizing the global throughput or predicting relevant network behaviors. This paper analyzes how common ML algorithms are able to model transmissions occurring in a typical wireless network scenario. In particular, we test the algorithms with our CN testbed to predict transmission estimated time of arrivals (ETAs) in different network setups. We compare these results with those obtained via scp, which is the typical Unix/Linux shell program used to exchange files. We show that all learning techniques significantly improve the goodness of ETA prediction, thus suggesting to embed such algorithms in future scp revisions.
Effects of retrieving childhood events on metamemory judgments depend on the questions you ask.

OBJECTIVE The more people retrieve childhood memories, the less favourably they evaluate their own memory. It has been argued that this might play a role in self-reports of amnesia. However, a limitation of previous studies addressing this phenomenon is that participants' judgments about their memory were based on a single item. DESIGN Students were randomly assigned to either of two conditions. In one condition, they were asked to retrieve nine negative childhood events, whereas in the other condition, participants were required to recall three events. METHOD After recall, students completed measures on memory accessibility and 'repression'. RESULTS Students who retrieved nine events rated their memories as less accessible, but also reported less repression than did students who retrieved three events. CONCLUSION The direction of retrieval effects on metamemory judgments depends on the way in which questions are framed.
On Cross-Correlation Evaluation Model of Internet Macroscopic Topology by Genetic Algorithm

Cross-correlation evaluation model, CCEM, was mainly studied to evaluate how much two different topologies are similar to each other in a quantitative way, and further used in evaluating whether a topology by an Internet topology model is close to real Internet or not. SLS (Signless Laplacian Spectra), is used to quantitatively identify the topology properties of the Internet generated by the model and the Internet out of real measuring. SLS eigenvectors could be gained out of this procedure, then a cross-correlation calculation was performed on the eigenvectors to give the difference identification in a quantitative way. With this, a recommended way of using the CCEM within a Genetic Algorithm was finally given.
INCIDENTAL VOCABULARY ACQUISITION IN A SECOND LANGUAGE

It is widely agreed that much second language vocabulary learning occurs incidentally while the learner is engaged in extensive reading. After a decade of intensive research, however, the incidental learning of vocabulary is still not fully understood, and many questions remain unsettled. Key unresolved issues include the actual mechanism of incidental acquisition, the type and size of vocabulary needed for accurate guessing, the degree of exposure to a word needed for successful acquisition, the efficacy of different word-guessing strategies, the value of teaching explicit guessing strategies, the influence of different kinds of reading texts, the effects of input modification, and, more generally, the problems with incidental learning. This article briefly surveys the empirical research that has been done on these issues in recent years.
To Flirt or Not to Flirt? Sexual Power at the Bargaining Table

We begin by exploring the lay belief that women can use flirtation to their advantage in professional contexts and contrast it with trained negotiators' negative views on flirtation. We then examine the impact of flirtation on negotiators' impression formation. We explore whether a flirtatious style aids women in the trade-off they often face between perceived likability and perceived competence. We discover both an upside and a downside to flirting at the bargaining table. Although flirtation appears to be positively related to women's likability, negotiators who flirted were judged to be less authentic than those who refrained from exercising their sexual power.
Assessing the Representativeness of Open Source Projects in Empirical Software Engineering Studies

BACKGROUND: Software engineering researchers have carried out many empirical studies on open source software (OSS) projects to understand the OSS phenomenon, and to develop better software engineering techniques. Many of these studies typically use only a few successful projects as study subjects. Recently, these studies have received criticisms and challenges on their representativeness on OSS projects. AIM: First, we aim to examine to what extent data extracted from successful projects are different from data extracted from the majority. If data extracted from successful projects are quite different from data extracted from the majority, approaches that are effective on successful projects may not be effective in general. Second, we aim to examine whether successful OSS projects are representative to the whole population of OSS. If they are not, conclusions that are drawn from only successful projects may reflect the OSS phenomenon partially. METHODOLOGY: We analyzed 11, 684 OSS projects that are hosted on Source Forge. When researchers select subjects, they typically select successful projects that are attractive to both users and developers. Considering this preference, we clustered these projects into four categories based their attractiveness to users and developers. Here, we use the K-means clustering technique to produce combined result. Furthermore, we selected eight indicators that are used in many existing studies (e.g., team sizes), and compared indicators that are extracted from different categories to investigate to what degree they are different. RESULT: For the first research aim, the result shows that 66.1% projects are under developing projects, 14.7% projects are user-preference projects, 14.2% projects are developer-preference projects, and only 5.0% projects are considered successful. For the second research aim, the result shows that all the eight analyzed indicators are highly unbalanced with the gamma distribution. Furthermore, the result reveals that users and developers of Source Forge have different perceptions on the development status defined by Source Forge. CONCLUSION: We conclude that successful projects are not representative to the whole population of OSS, and data extracted from successful projects are quite different from data extracted from the majority. The result implies that conclusions drawn from only a few successful projects may be challenged. This work is important to allow researchers to refine conclusions of existing studies, and to better understand and to carefully select OSS project subjects for their future empirical experiments.
Thriving in Adolescence

This study assesses if correspondence existed between concepts scholars use to discuss positive youth development (PYD) and terms used by practitioners, parents, and youth to discuss exemplary PYD, or thriving. Qualitative and quantitative analyses of 173 interviews about the meaning of thriving found no significant commonality between the terms used in the scholarly literature and the specific words or phrases used by the adult and youth participants. However, the terms generated by the adults and youthwere able to be grouped into categories that reflect the general concepts used in the PYD literature (e.g., the five Cs ofcompetence, confidence, connection, character, caring, and the sixth C, contribution). Applications to public education youth programs are discussed.
Mechanism of Actin-Based Motility

Spatially controlled polymerization of actin is at the origin of cell motility and is responsible for the formation of cellular protrusions like lamellipodia. The pathogens Listeria monocytogenes and Shigella flexneri, which undergo actin-based propulsion, are acknowledged models of the leading edge of lamellipodia. Actin-based motility of the bacteria or of functionalized microspheres can be reconstituted in vitro from only five pure proteins. Movement results from the regulated site-directed treadmilling of actin filaments, consistent with observations of actin dynamics in living motile cells and with the biochemical properties of the components of the synthetic motility medium.
Capacity vs. delivery delay in MANETs with power control and f-cast relay

A lot of works have been dedicated towards understanding the relationship between throughput capacity and packet delay in mobile ad hoc networks (MANETs). However, nearly all these works either assume a localized transmission range, or report the relationship between throughput capacity and packet delay only in terms of the number of users. It remains largely unknown for such a fundamental relationship in terms of other network parameters, like the packet redundancy and node transmission range. As a first step towards this end, in this paper we derive closed-from expressions for throughput capacity and delivery delay under a general setting of node transmission range and also a generalized two-hop relay with limited packet redundancy. Extensive numerical results are further provided to explore how throughput capacity varies with delivery delay in terms of various network parameters, such as the number of users, the packet redundancy limit, and the node transmission range, etc.
Recognition of the Measles Virus Nucleocapsid as a Mechanism of IRF-3 Activation

ABSTRACT The mechanisms of cellular recognition for virus infection remain poorly understood despite the wealth of information regarding the signaling events and transcriptional responses that ensue. Host cells respond to viral infection through the activation of multiple signaling cascades, including the activation of NF-κB, c-Jun/ATF-2 (AP-1), and the interferon regulatory factors (IRFs). Although viral products such as double-stranded RNA (dsRNA) and the processes of viral binding and fusion have been implicated in the activation of NF-κB and AP-1, the mechanism(s) of IRF-1, IRF-3, and IRF-7 activation has yet to be fully elucidated. Using recombinant measles virus (MeV) constructs, we now demonstrate that phosphorylation-dependent IRF-3 activation represents a novel cellular detection system that recognizes the MeV nucleocapsid structure. At low multiplicities of infection, IRF-3 activation is dependent on viral transcription, since UV cross-linking and a deficient MeV containing a truncated polymerase L gene failed to induce IRF-3 phosphorylation. Expression of the MeV nucleocapsid (N) protein, without the requirement for any additional viral proteins or the generation of dsRNA, was sufficient for IRF-3 activation. In addition, the nucleocapsid protein was found to associate with both IRF-3 and the IRF-3 virus-activated kinase, suggesting that it may aid in the colocalization of the kinase and the substrate. Altogether, this study suggests that IRF-3 recognizes nucleocapsid structures during the course of an MeV infection and triggers the induction of interferon production.
Doctoral and Postdoctoral Education in Science and Engineering: Europe in the international competition

In this article, we discuss the recent evolutions of science and engineering doctoral and postdoctoral education in Europe. Indeed, Ph.Ds are crucial to the conduct of research and innovation in the national innovation systems, as they provide a large amount of input into creating the competitive advantage, notably through basic research. First, we show that Asia, and notably China, is producing more Ph.Ds than the United States and Europe. In many EU countries, the number of Ph.Ds has levelled off or even declined recently in many natural sciences and engineering fields. Second, we discuss the European situation in the international competition for talents. We study the European brain drain question, mainly at the doctoral and postdoctoral level. We find that there is an asymmetry in the flows of Ph.D students and postdoctorates between Europe and the United States, at the advantage of this latter country. These two points — production of Ph.Ds, international flows of doctorates and postdoctorates — lead us to be concerned about the future growth and innovation in Europe. In conclusion, we outline some European policy responses in the perspective of building the European Research Area and the European Higher Education Area.
Complex geometry of conifolds and a 5-brane wrapped on a 2-sphere

We investigate solutions of type II supergravity which have the product ℝ1,3×M6 structure with non-compact M6 factor and which preserve at least four supersymmetries. In particular, we consider various conifolds and the N = 1 supersymmetric `NS5-brane wrapped on a 2-sphere' solution recently discussed in hep-th/0008001. In all of these cases, we explicitly construct the complex structures, and the Kähler and parallel (3,0)-forms of the corresponding M6. In addition, we verify that the above solutions preserve, respectively, eight and four supersymmetries of the underlying type II theory. We also demonstrate that the ordinary and fractional D3-brane (5-brane wrapped on a 2-cycle) solutions on singular, resolved and deformed conifolds, and the (S-dual of) NS5-brane wrapped on 2-sphere can be obtained as special cases from a universal ansatz for the supergravity fields, i.e. from a single one-dimensional action governing their radial evolution. We show that like the 3-branes on conifolds, the NS5-brane on a 2-sphere background can be found as a solution of a first-order system following from a superpotential.
The Evolutionary Stability of Cooperation

Is cooperation without central authority stable? If so, how robust is it? Despite what might be the conventional wisdom, The Evolution of Cooperation did not solve this problem deductively. In fact, results obtained later by others seem to have contradicted the book's main message. Reexamining this exceptionally influential work yields a new picture. Part of Axelrod's evolutionary story turns out to be false. But the main intuition, that retaliatory strategies of conditional cooperation are somehow advantaged, proves correct in one specific and significant sense: Under a standard evolutionary dynamic these strategies require the minimal frequency to stabilize. Hence, they support the most robust evolutionary equilibrium: the easiest to reach and retain. Moreover, the less efficient a strategy, the larger is its minimal stabilizing frequency; Hobbesian strategies of pure defection are the least robust. Our main theorems hold for a large class of games that pose diverse cooperation problems: prisoner's dilemma, chicken, stag hunt, and many others.
Multireference TDOA-based source localization

Time difference of arrival (TDOA)-based methods usually achieve the most accurate source localization in passive systems. In these methods, one of the sensors is assigned as the reference and the TDOA of the others with respect to the reference is measured. The source location is estimated by processing these TDOAs. In this paper, a multireference maximum likelihood (ML)-Taylor algorithm is proposed in order to decrease the source localization error of the TDOA methods. In the proposed algorithm, TDOAs are measured assuming 2 different reference sensors, and then the ML objective function of this multireference TDOA algorithm is derived and solved using Taylor series linearization. The developed method is evaluated regarding a 2-dimensional space with some different but deterministic sensor locations. Monte Carlo simulation is used to evaluate the proposed solution. The simulation results show that the proposed method has better performance relative to the other traditional TDOA-based algorithms.