Miracle-dz/UniFAR-FTUs huggingface dataset:
L1 Interaction with Ankyrin Regulates Mediolateral Topography in the Retinocollicular Projection

Dynamic modulation of adhesion provided by anchorage of axonal receptors with the cytoskeleton contributes to attractant or repellent responses that guide axons to topographic targets in the brain. The neural cell adhesion molecule L1 engages the spectrin-actin cytoskeleton through reversible linkage of its cytoplasmic domain to ankyrin. To investigate a role for L1 association with the cytoskeleton in topographic guidance of retinal axons to the superior colliculus, a novel mouse strain was generated by genetic knock-in that expresses an L1 point mutation (Tyr1229His) abolishing ankyrin binding. Axon tracing revealed a striking mistargeting of mutant ganglion cell axons from the ventral retina, which express high levels of ephrinB receptors, to abnormally lateral sites in the contralateral superior colliculus, where they formed multiple ectopic arborizations. These axons were compromised in extending interstitial branches in the medial direction, a normal response to the high medial to low lateral SC gradient of ephrinB1. Furthermore, ventral but not dorsal L1(Y1229H) retinal cells were impaired for ephrinB1-stimulated adhesion through β1 integrins in culture. The retinocollicular phenotype of the L1(Tyr1229His) mutant provides the first evidence that L1 regulates topographic mapping of retinal axons through adhesion mediated by linkage to the actin cytoskeleton and functional interaction with the ephrinB/EphB targeting system.
Constructing Expertise: Terrorist Recruitment and “Talent Spotting” in the PIRA, Al Qaeda, and ISIS

ABSTRACT The academic literature is divided with regard to whether terrorist recruits are dangerous masterminds, “malevolently creative,” and capable of perpetrating well-planned mass casualty attacks in the heart of European capitals. Or whether they are imbeciles, incapable of carrying out the most basic tasks, who mostly end up blowing themselves up by accident. This duality about the capabilities of terrorists is reflected in analyses of terrorist incidents. In fact, both depictions of terrorist recruits are accurate. Acuity and professionalism are not movement dependent (the same group may attract a variety of recruits) and might, instead, reflect a recruitment cycle that terrorist groups experience—one that alternates between labor-intensive and expertise-intensive periods of recruitment. The phases may shift because of external pressures (periods of territorial expansion/contraction) and opportunities (need for better quality recruits) with associated shifts in how groups use propaganda to attract a different quality of recruit during different periods of time. A possible first step toward hindering terrorist recruitment is to better understand the ways in which terrorist organizations work—where and when they recruit, whom they target, and the different propaganda messages used for selective/targeted recruitment. A clearer picture of the process could provide opportunities to counter a group's appeal, replenish their ranks, and inoculate vulnerable populations against recruitment. Case studies of three different terrorist organizations (Al Qaeda, the Islami State in Iraq and Syria [ISIS], and the Provisional Irish Republican Army [PIRA]) presented here posit that there exists a terrorism “recruitment cycle” that alternates between labor and expertise focus, uses different recruitment strategies and different propaganda messaging depending on this cycle.
Orthostatic-induced Hypotension Attenuates Cold Pressor Pain Perception

In recent years, numerous studies have established a connection between blood pressure and nocioception. While this connection is well documented in the literature, its underlying physiological mechanisms have yet to be elucidated. Much attention has focused on the relationship between cardiovascular regulatory centers and nocioception, yet the intricacies of this relationship have not been fully explored. Therefore, the purpose of this investigation was to examine the role of the baroreflex system as a modulator of pain perception. Twenty normotensive males participated in two laboratory sessions. Time to cold pain threshold and pain tolerance was measured at rest during the first visit. On visit two, blood pressure was orthostatically manipulated via tilt table at postures 90o, 120o, and 180o. Orthostatic manipulation significantly lowered systolic blood pressure (SBP), pain threshold, and pain tolerance from seated baseline at 120o and 180o. The regression models for baroreceptor reflex sensitivity (BRS) assessed during seated baseline and at 120o and 180o revealed a significant negative beta weight for the effect of SBP. A significant negative beta weight for the effects of BRS, SBP, and their interaction was observed at 90o. In conclusion, orthostatic baroreceptor activation appears to exert an inhibitory effect on the brain that decreases pain sensitivity. This article is available at The Cupola: Scholarship at Gettysburg College: http://cupola.gettysburg. edu/healthfac/32 Orthostatic Hypotension and Pain Perception 21 Journal of Exercise Physiologyonline (JEPonline) Volume 13 Number 1 February 2010 Managing Editor Tommy Boone, PhD, MPH Editor-in-Chief Jon K. Linderman, PhD Review Board Todd Astorino, PhD Julien Baker, PhD Tommy Boone, PhD Eric Goulet, PhD Robert Gotshall, PhD Alexander Hutchison, PhD M. Knight-Maloney, PhD Len Kravitz, PhD James Laskin, PhD Derek Marks, PhD Cristine Mermier, PhD Chantal Vella, PhD Ben Zhou, PhD Official Research Journal of the American Society of Exercise Physiologists (ASEP) ISSN 1097-975 Systems Physiology Cardiopulmonary Orthostatic-induced Hypotension Attenuates Cold Pressor Pain Perception KAREN WONDERS and DANIEL DRURY Wright State University, Department of Health, Physical Education and Recreation, Dayton, OH 45435 USA, Gettysburg College, Department of Health Sciences, Gettysburg, PA, USA
Reactivation of autophagy by spermidine ameliorates the myopathic defects of collagen VI-null mice

Autophagy is a self-degradative process responsible for the clearance of damaged or unnecessary cellular components. We have previously found that persistence of dysfunctional organelles due to autophagy failure is a key event in the pathogenesis of COL6/collagen VI-related myopathies, and have demonstrated that reactivation of a proper autophagic flux rescues the muscle defects of Col6a1-null (col6a1−/−) mice. Here we show that treatment with spermidine, a naturally occurring nontoxic autophagy inducer, is beneficial for col6a1−/− mice. Systemic administration of spermidine in col6a1−/− mice reactivated autophagy in a dose-dependent manner, leading to a concurrent amelioration of the histological and ultrastructural muscle defects. The beneficial effects of spermidine, together with its being easy to administer and the lack of overt side effects, open the field for the design of novel nutraceutical strategies for the treatment of muscle diseases characterized by autophagy impairment.
THE STATUS QUO OF TEACHER-TRAINING COURSES IN THE IRANIAN EFL CONTEXT: A FOCUS ON MODELS OF PROFESSIONAL EDUCATION AND DYNAMIC ASSESSMENT

Given that Teacher-Training Courses (TTC’s) have responsibility for assisting prospective teachers with building up a repertoire of technical and pedagogic knowledge, the systematically evaluation of such courses is regarded as seminal (Lynch, 2003 and Peacock, 2009). Therefore, the present study is an attempt to (a) probe into the way professional expertise is acquired by preservice Iranian EFL teachers, (b) analyze the instructional content of TTC’s currently held in Iran, with a focus on teachings on Dynamic Assessment (DA), and (c) examine preservice teachers’ and TTC trainers’ opinions about the TTC’s. To this end, 9 purposefully selected TTC’s were observed, employing participant observation, and content analyses were carried out on their syllabi. Also, 107 TTC participants filled out a questionnaire, and 14 TTC instructors were interviewed; the sampling of the TTC participants and instructors was nonprobability convenient. Results of descriptive statistics showed that accounting for 84.73% of all the instructional attempts, the craft model was the most frequently prevalent model of teacher learning. Content analyses and preservice teacher questionnaire results signified that writing skill was marginalized in all the courses, and none of them included instructions on DA in their syllabi. Open, selective, and axial coding as well as content analyses of the collected data gave rise to eight themes delineating major areas fueling the current research-practice divide in the TTC syllabi. Findings of the study provide an opportunity to examine the status quo, strengths, and weaknesses of the TTC’s. The eight identified impediments to the employment of research in pedagogy could help reach a framework for factors that might induce TTC organizers to disregard the implication of relevant research findings for the courses they run.
Predictor and moderator effects in the treatment of oppositional defiant disorder in pediatric primary care.

OBJECTIVE To examine predictors and moderators of parent-training outcomes for treatment of Oppositional Defiant Disorder (ODD) in pediatric primary care. METHODS Parents of 117 children with ODD, ages 3-6 years, seen in primary care received either a minimal intervention bibliotherapy treatment (MIT), or a 12-session parenting program led by a nurse or psychologist. RESULTS More initial total life stress, parenting distress, internalizing problems, functional impairment, and difficult temperament were associated with more improvement, but families scoring lower on those variables had fewer behavior problems at posttreatment and follow-up. Gender was a significant moderator, with more improvement for girls than boys in the nurse-led group but more improvement for boys than girls in the MIT group. Less well-educated mothers treated by psychologists showed the greatest change. CONCLUSIONS Predictors and moderators may play a role in deciding, which families receive a particular form of treatment for ODD in primary care.
Planning characters' behaviour in interactive storytelling

In this paper, we describe a method for implementing the behaviour of artificial actors in the context of interactive storytelling. We have developed a fully implemented prototype based on the Unreal Tournament™ game engine, and carried experiments with a simple sitcom-like scenario. We discuss the central role of artificial actors in interactive storytelling and how real-time generation of their behaviour participates in the creation of a dynamic storyline. We follow previous work describing the behaviour of artificial actors through AI planning formalisms, and adapt it to the context of narrative representation. In this context, the narrative equivalent of a character’s behaviour consists in its role. The set of possible roles for a given actor is represented as a Hierarchical Task Network (HTN). The system uses HTN planning to dynamically generate the character roles, by interleaving planning and execution, which supports dynamic interaction between actors, as well as user intervention in the unfolding plot. Finally, we present several examples of short plots and situations generated by the system from the dynamic interaction of artificial actors.
An improved trusted cloud computing platform model based on DAA and privacy CA scheme

Security and privacy are two prime barriers to adoption of the cloud computing. To address this problem on Infrastructure-as-a-Service model, a trusted cloud computing platform model has been proposed to provide a closed box execution environment that guarantees confidential execution of guest virtual machines. However this model has significant drawbacks that it relies on the trusted third party outside of the cloud circumstance too much. In this paper we show how to address this issue based on the neutral feature of the Trusted Platform Module. By moving the responsibility of managing trusted platforms from the trusted third party to the trusted platforms of Infrastructure-as-a-Service model, our improved TCCP model achieves higher availability, reliability and safety.
Hidden Markov Models for Lithological Well Log Classification

The aim of this study is to explore the usefulness of hidden Markov models for lithological classification of geophysical measurements in boreholes. Standard statistical methods like linear and quadratic discriminant or cluster analysis treat the individual measurement points of well logs as independent samples of the underlying distribution. With hidden Markov models (HMM) the knowledge of statistical dependency between successive data points in a well log can be incorporated in the classification process. The sequence of lithological classes is modelled as a discrete, finite, homogeneous, first order Markov chain of transitions between states. This state sequence can be unobserved or is generally hidden from the observer. The only necessary information about the hidden state sequence is an observed sequence of state-dependent outputs. This output information is used to estimate the hidden state sequence which most probably has caused the given output sequence. The performance of HMM is evaluated on simulated data and on a real data set from eight wells near Berlin (Germany) with final depths between 60 and 140 metres. The results are compared with the outcome of the quadratic discriminant analysis.
Environmental Research and Public Health Long Non-coding Rna as Potential Biomarker for Prostate Cancer: Is It Making a Difference?

Whole genome transcriptomic analyses have identified numerous long non-coding RNA (lncRNA) transcripts that are increasingly implicated in cancer biology. LncRNAs are found to promote essential cancer cell functions such as proliferation, invasion, and metastasis, with the potential to serve as novel biomarkers of various cancers and to further reveal uncharacterized aspects of tumor biology. However, the biological and molecular mechanisms as well as the clinical applications of lncRNAs in diverse diseases are not completely understood, and remain to be fully explored. LncRNAs may be critical players and regulators in prostate cancer carcinogenesis and progression, and could serve as potential biomarkers for prostate cancer. This review focuses on lncRNA biomarkers that are already available for clinical use and provides an overview of lncRNA biomarkers that are under investigation for clinical development in prostate cancer.
Secure software update and IP protection for untrusted devices in the Internet of Things via physically unclonable functions

We are on the brink of a new era, the Internet of Things. Security threats will rise with an increasing number of devices, since typical sensor nodes refrain from resource intense, seasoned security measures. Hence, we have to assume that sensor nodes will receive software updates more frequently. Particularly IP providers in the emerging market of specialized software will want their software protected during an update process. We propose a novel protocol by integrating different trust establishing techniques, to allow secure software updates on nodes already infected with malware. In short, a device has to prove the erasure of its memory within a time constraint and a physically unclonable function binds the newly downloaded software IP to the target platform. We surveyed several commercial smart home systems and analysed the security of our protocol. Compared to existing solutions, our protocol offers stronger IP protection under a more powerful attacker model, while the implementation costs are comparable to those of the existing protocols.
Regulation of Amphiregulin Gene Expression by β-Catenin Signaling in Human Hepatocellular Carcinoma Cells: A Novel Crosstalk between FGF19 and the EGFR System

Hepatocellular carcinoma (HCC) is the most prevalent liver tumor and a deadly disease with limited therapeutic options. Dysregulation of cell signaling pathways is a common denominator in tumorigenesis, including hepatocarcinogenesis. The epidermal growth factor receptor (EGFR) signaling system is commonly activated in HCC, and is currently being evaluated as a therapeutic target in combination therapies. We and others have identified a central role for the EGFR ligand amphiregulin (AR) in the proliferation, survival and drug resistance of HCC cells. AR expression is frequently up-regulated in HCC tissues and cells through mechanisms not completely known. Here we identify the β-catenin signaling pathway as a novel mechanism leading to transcriptional activation of the AR gene in human HCC cells. Activation of β-catenin signaling, or expression of the T41A β-catenin active mutant, led to the induction of AR expression involving three specific β-catenin-Tcf responsive elements in its proximal promoter. We demonstrate that HCC cells expressing the T41A β-catenin active mutant show enhanced proliferation that is dependent in part on AR expression and EGFR signaling. We also demonstrate here a novel cross-talk of the EGFR system with fibroblast growth factor 19 (FGF19). FGF19 is a recently identified driver gene in hepatocarcinogenesis and an activator of β-catenin signaling in HCC and colon cancer cells. We show that FGF19 induced AR gene expression through the β-catenin pathway in human HCC cells. Importantly, AR up-regulation and EGFR signaling participated in the induction of cyclin D1 and cell proliferation elicited by FGF19. Finally, we demonstrate a positive correlation between FGF19 and AR expression in human HCC tissues, therefore supporting in clinical samples our experimental observations. These findings identify the AR/EGFR system as a key mediator of FGF19 responses in HCC cells involving β-catenin signaling, and suggest that combined targeting of FGF19 and AR/EGFR may enhance therapeutic efficacy.
A JAZ Protein in Astragalus sinicus Interacts with a Leghemoglobin through the TIFY Domain and Is Involved in Nodule Development and Nitrogen Fixation

Leghemoglobins (Lbs) play an important role in legumes-rhizobia symbiosis. Lbs bind O2 and protect nitrogenase activity from damage by O2 in nodules, therefore, they are regarded as a marker of active nitrogen fixation in nodules. Additionally, Lbs are involved in the nitric oxide (NO) signaling pathway, acting as a NO scavenger during nodule development and nitrogen fixation. However, regulators responsible for Lb expression and modulation of Lb activity have not been characterized. In our previous work, a Jasmonate-Zim-domain (JAZ) protein interacting with a Lb (AsB2510) in Astragalus sinicus was identified and designated AsJAZ1. In this study, the interaction between AsJAZ1 and AsB2510 was verified using a yeast two-hybrid system and in vitro Glutathione S-transferase (GST) pull-down assays, resulting in identification of the interaction domain as a TIFY (previously known as zinc-finger protein expressed in inflorescence meristem, ZIM) domain. TIFY domain is named after the most conserved amino acids within the domain. Bimolecular fluorescence complementation (BiFC) was used to confirm the interaction between AsJAZ1 and AsB2510 in tobacco cells, demonstrating that AsJAZ1-AsB2510 interaction was localized to the cell membrane and cytoplasm. Furthermore, the expression patterns and the symbiotic phenotypes of AsJAZ1 were investigated. Knockdown of AsJAZ1 expression via RNA interference led to decreased number of nodules, abnormal development of bacteroids, accumulation of poly-x-hydroxybutyrate (PHB) and loss of nitrogenase activity. Taken together, our results suggest that AsJAZ1 interacts with AsB2510 and participates in nodule development and nitrogen fixation. Our results provide novel insights into the functions of Lbs or JAZ proteins during legume-rhizobia symbiosis.
Kernel density-based acoustic model with cross-lingual bottleneck features for resource limited LVCSR

Conventional acoustic models, such as Gaussian mixture models (GMM) or deep neural networks (DNN), cannot be reliably estimated when there are very little speech training data, e.g. less than 1 hour. In this paper, we investigate the use of a non-parametric kernel density estimation method to predict the emission probability of HMM states. In addition, we introduce a discriminative score calibrator to improve the speech class posteriors generated by the kernel density for speech recognition task. Experimental results on the Wall Street Journal task show that the proposed acoustic model using cross-lingual bottleneck features signiﬁcantly outperforms GMM and DNN models for limited training data case.
Waiting Time Variance in Polling Systems

In this paper, we develop a general expression for the second moment of waiting time for polling systems with either an exhaustive or gated service policy. We obtain a closed form expression for the second moment of waiting time for the special case of systems with two identical stations. This result is used to show that the behavior of the first two moments can be very different. Specifically, we show that while the expected waiting time is always smaller under the exhaustive policy, the same does not hold for waiting time variance. In fact, we characterize conditions for which the waiting time variance under the exhaustive policy is infinitely larger than the variance under the gated policy. For systems with more than two stations, we present computational results to extend these conclusions. We use these results to show that the difference in waiting time variance between the two policies is not monotonic in the number of stations. For asymmetric systems, we also show that the gated policy can have, for certain stations, both a smaller mean and variance of waiting time.
Negation Scope Detection for Twitter Sentiment Analysis

The paper describes the first sophisticated negation scope detection system for Twitter sentiment analysis. The system has been evaluated both on existing corpora from other domains and on a corpus of English Twitter data (tweets) annotated for negation. It produces better results than what has been reported in other domains and improves the performance on tweets containing negation when incorporated into a state-of-the-art Twitter sentiment analyser.
A Novel Classifier-Independent Feature Selection Algorithm for Imbalanced Datasets

A novel classifier-independent feature selection algorithm based on the posterior probability is proposed for imbalanced datasets. First, an imbalanced factor is introduced and computed by Parzen-window estimation. The middle point of Tomek links is chosen as the initial point. Accordingly, this algorithm is iterated to find out the boundary points which have the equality of posterior probability. Through the project computation on the normal vectors of these points, the weight of each feature can be obtained, which actually indicates the importance degree of each feature. The experimental results on 3 real-word datasets demonstrate that this proposed algorithm can not only reduce the computational cost but also overcome the shortcoming that the majority class may be detected well but the minority class may be ignored in the conventional feature selection algorithm.