Miracle-dz/UniFAR-FTUs huggingface dataset:
Fgfr signaling is required as the early eye field forms to promote later patterning and morphogenesis of the eye

Background: A major step in eye morphogenesis is the transition from optic vesicle to optic cup, which occurs as a ventral groove forms along the base of the optic vesicle. A ventral gap in the eye, or coloboma, results when this groove fails to close. Extrinsic signals, such as fibroblast growth factors (Fgfs), play a critical role in the development and morphogenesis of the vertebrate eye. Whether these extrinsic signals are required throughout eye development, or within a defined critical period remains an unanswered question. Results: Here we show that an early Fgf signal, required as the eye field is first emerging, drives eye morphogenesis. In addition to triggering coloboma, inhibition of this early Fgf signal results in defects in dorsal‐ventral patterning of the neural retina, particularly in the nasal retina, and development of the periocular mesenchyme (POM). These processes are unaffected by inhibition of Fgfr signaling at later time points. Conclusions: We propose that Fgfs act within an early critical period as the eye field forms to promote development of the neural retina and POM, which subsequently drive eye morphogenesis. Developmental Dynamics 243:663–675, 2014. © 2014 Wiley Periodicals, Inc.
Ensuring effectiveness in our front‐line leaders

Clearly, the role of front‐line leader (often known as supervisor, team leader, foreman and so on) is a critical, challenging and often unappreciated role. However, the role must be performed effectively if work teams are to optimise their effectiveness. This paper argues that four practices, easily stated but difficult to fully implement, are required in order to fully develop the front‐line leadership function. The practices are: implement a well‐focused system of goals and feedback; employ rigorous leadership selection processes (including the removal of ineffective leaders); maintain well‐developed and evolving human resource management systems; and implement training and development as an ongoing process. The rationale for each practice is provided as well as examples from experience.
Building a Tool for Annotating Reference in Discourse

We discuss the development of a system for marking several types of reference to facilitate the analysis of reference in discourse. The tool is designed to be used in three applicationsi generating training data for machine learning of co-reference relations, evaluating iheories of referring expression generation and resolution in texts, and developing theories for understanding reference in dialogs. The need to mark any of a broad set of relations which may span several levels of discourse structure drives the system architecture. The system has the abilityto collect statistics over encoded relations and meastwe inter-coder reliability, and includes tools to increase the accuracy of the user's markings by highlighting the di.u:repancies between two sets of markings. Using parsed corpora as the input further reduces the human workload and increases reliability.
The Bem Sex-Role Inventory

Pedhazur and Tetenbaum speculated that factor structures from self-ratings of the Bem Sex-Role Inventory (BSRI) personality traits would be different from factor structures from desirability ratings of the same traits. To explore this hypothesis, both desirability ratings of BSRI traits (both for a man and for a woman) and self-ratings were obtained from the same sample and factor analyzed. Factor analyses performed on the three sets of ratings of the 40 BSRI traits (self-ratings, desirability ratings for a man, and desirability ratings for a woman) confirmed that the factors across ratings were diverse. Thus, the underlying constructs must be studied independently. Predictive discriminant analyses replicated the finding that two traits alone (Masculine and Feminine) provided nearly all of the discrimination of males and females in the sample when self-ratings were employed. Also, predictive discriminant analyses revealed that the classification of participants into gender groups was very accurate using self-ratings but deteriorated remarkably when using the desirability ratings.
Furuta Pendulum -- A Tensor Product Model-Based Design Approach Case Study

The main purpose of this paper to demonstrate how to apply basic convex optimization on robot controller design specifically on the example of the inverted Furuta pendulum. The work shows how convex optimization can be implemented and that the Tensor Product-based approach could be easily applied for robot stabilization. The design stages are shown from the quasi Linear Parameter Varying form of the Lagrange-Euler equations through giving a deeper insight into Tensor Product model transformation until the optimal control problem formulation via Linear Matrix Inequalities. The design method is well supported by TPtool and CVX Mat Lab toolboxes that are both convenient to use. Numerical simulations have also been performed to show the power of the computational solution of robot stabilization.
Sex-Role Stereotyping for Selected Sport and Physical Activities across Age Groups

This investigation was designed to assess sex-role stereotyping across age groups. Participants (N = 668) were girls and boys, students from Grades 3, 5, 8, and 10 at local public schools. All participants completed the Sport and Physical Activities Questionnaire on which were displayed pictures of 31 sport and physical activities. Participants were instructed to designate each activity as a boys' activity, a girls' activity, or a boys' and girls' activity. Chi-square analysis showed age-related differences in distribution of stereotyping of the activities. Over age groups there were more discrepancies between boys' and girls' ratings of activities as sex-specific. These findings suggest that sex-role stereotyping of sports and physical activities becomes more predominant across age groups.
Biologically Plausible Neural Model for the Recognition of Biological Motion and Actions

Abstract : The visual recognition of complex movements and actions is crucial for communications and survival in many species. Remarkable sensitivity and robustness of biological motion perception have been demonstrated in psychophysical experiments. In recent years, neurons and cortical areas involved in action recognition have been identified in neurophysiological and imaging studies. However, the detailed neural mechanisms that underlie the recognition of such complex movement patterns remain largely unknown. This paper reviews the experimental results and summarizes them in terms of a biologically plausible neural model. The model is based on the key assumption that action recognition is based on learned prototypical patterns and exploits information from the ventral and dorsal pathway. The model makes specific predictions that motivate new experiments.
Previous Cocaine Exposure Makes Rats Hypersensitive to Both Delay and Reward Magnitude

Animals prefer an immediate over a delayed reward, just as they prefer a large over a small reward. Exposure to psychostimulants causes long-lasting changes in structures critical for this behavior and might disrupt normal time-discounting performance. To test this hypothesis, we exposed rats to cocaine daily for 2 weeks (30 mg/kg, i.p.). Approximately 6 weeks later, we tested them on a variant of a time-discounting task, in which the rats responded to one of two locations to obtain reward while we independently manipulated the delay to reward and reward magnitude. Performance did not differ between cocaine-treated and saline-treated (control) rats when delay lengths and reward magnitudes were equal at the two locations. However, cocaine-treated rats were significantly more likely to shift their responding when we increased the delay or reward size asymmetrically. Furthermore, they were slower to respond and made more errors when forced to the side associated with the lower value. We conclude that previous exposure to cocaine makes choice behavior hypersensitive to differences in the time to and size of available rewards, consistent with a general effect of cocaine exposure on reward valuation mechanisms.
Role of the VP16-Binding Domain of vhs in Viral Growth, Host Shutoff Activity, and Pathogenesis

ABSTRACT The virion host shutoff (vhs) protein of herpes simplex virus type 1 causes the degradation of host and viral mRNA immediately upon infection of permissive cells. vhs can interact with VP16 through a 20-amino-acid binding domain, and viruses containing a deletion of this VP16-binding domain of vhs (Δ20) and a corresponding marker rescue (Δ20R) were constructed and characterized. Transient-transfection assays showed that this domain was dispensable for vhs activity. The Δ20 recombinant virus, however, was unable to induce mRNA degradation in the presence of actinomycin D, while degradation induced by Δ20R was equivalent to that for wild-type virus. Δ20, Δ20R, and KOS caused comparable RNA degradation in the absence of actinomycin D. Western blot analysis of infected cells indicated that comparable levels of vhs were expressed by Δ20, Δ20R, and KOS, and there was only a modest reduction of vhs packaging in Δ20. Immunoprecipitation of protein from cells infected with Δ20 and Δ20R showed equivalent coprecipitation of vhs and VP16. Pathogenesis studies with Δ20 showed a significant decrease in replication in the corneas, trigeminal ganglia, and brains, as well as a significant reduction in clinical disease and lethality, but no significant difference in the establishment of, or reactivation from, latency compared to results with KOS and Δ20R. These results suggest that the previously described VP16-binding domain is not required for vhs packaging or for binding to VP16. It is required, however, for RNA degradation activity of tegument-derived vhs and wild-type replication and virulence in mice.
Curved trajectory tracking for surface vessel formations

Following curved trajectories with a formation of vehicles can be accomplished by defining the formation positions relative to the trajectory. Using a Serret-Frenet frame results in problems along straight lines and at inflection points; we suggest to use a geodesic reference frame instead. Conditional integrators are used to obtain robustness against constant external disturbances. Simulation results are provided to illustrate the effectiveness of the proposed method.
Preclinical assessment of the proinflammatory potential of microbicide candidates

The efficacy of a microbicide depends on the balance between its specific activity and its safety. The experience with nonoxynol-9, the first microbicide to be tested in clinical trials, provides a good example of a compound with high in-vitro activity and poor clinical performance, possibly because of underestimated local safety issues. In order to identify compounds that may induce epithelial toxicity and inflammation early in drug development, we have established a preclinical evaluation system based on the assessment of cytotoxicity, cytokine secretion, and tissue inflammatory reaction using a human vaginal cell line (VK-2/E6E7) and a refined rabbit vaginal irritation model. Evaluated through this system, nonoxynol-9 displayed high cytotoxicity and proinflammatory activity. VK-2 cells incubated for 6 h with nonoxynol-9 released significant amounts of IL-1, IL-6 and IL-8. Gels containing 2 and 4% nonoxynol-9, administered to female rabbits intravaginally for 3 days, induced a potent inflammatory reaction evidenced by high levels of IL-1b and CD3+ T cells in cervicovaginal lavages and a significant influx of CD4 and nuclear factor kappa B cells into mucosal and submucosal tissues. Interestingly, cervicovaginal epithelium exposed to nonoxynol-9 also showed high levels of active nuclear factor kappa B immunoreactivity. This combined, sequential, preclinical evaluation system based on VK-2 cells in culture and a refined rabbit vaginal irritation model represents a valuable tool to assess the local safety profile of anti-HIV microbicide candidates.
A latent force model for describing electric propagation in deep brain stimulation: A simulation study

Deep brain stimulation (DBS) is a neurosurgical method used to treat symptoms of movement disorders by implanting electrodes in deep brain areas. Often, the DBS modeling approaches found in the literature assume a quasi-static approximation, and discard any dynamic behavior. Nevertheless, in a real DBS system the stimulus corresponds to a wave that changes as a function of time. It is clear that DBS demands an approach that takes into account the time-varying behavior of the input stimulus. In this work, we present a novel latent force model for describing the dynamic electric propagation occurred during DBS. The performance of the proposed model was studied by simulations under different conditions. The results show that our approach is able to take into account the time variations of the source and the produced field. Moreover, by restricting our model it is possible to obtain solutions for electrostatic formulations, here experimental results were compared with the finite element method. Additionally, our approach allows a solution to the inverse problem, which is a valuable clinical application allowing the appropriate tuning of the DBS device by the expert physician.
Individual Differences in Search Behavior For a Nondurable

Subjects acquired information on, chose, and consumed one of five health breads once a week for six weeks. The effects of individual differences on information acquisition and recall of package information were studied. Experience during the experiment was highly related to the amount of external search and recall of package information. Information-processing style was also related to external search.
Combination of Time-of-Flight depth and stereo using semiglobal optimization

A growing number of modern computer vision applications like object recognition, collision avoidance and scene understanding demand accurate and dense 3D representations of their environment. To improve existing procedures for 3D data acquisition this paper proposes a novel method for sensor combination on a stereo and a Time-of-Flight camera system. By calibrating the two sensor systems to each other, valid measurements from the 2.5D Time-of-Flight sensor are converted to disparity guesses within the stereo system. The disparity guesses from the Time-of-Flight data constrain the correspondence search results from the stereo matching algorithm. It is empirically shown, that the proposed method effectively enhance the results from stereo vision, especially in structureless areas where stereo correspondence search fails. The method is evaluated on the camera system of the service robot Care-O-bot® 3.
Interhemispheric synchrony in the neonatal EEG revisited: activation synchrony index as a promising classifier

A key feature of normal neonatal EEG at term age is interhemispheric synchrony (IHS), which refers to the temporal co-incidence of bursting across hemispheres during trace alternant EEG activity. The assessment of IHS in both clinical and scientific work relies on visual, qualitative EEG assessment without clearly quantifiable definitions. A quantitative measure, activation synchrony index (ASI), was recently shown to perform well as compared to visual assessments. The present study was set out to test whether IHS is stable enough for clinical use, and whether it could be an objective feature of EEG normality. We analyzed 31 neonatal EEG recordings that had been clinically classified as normal (n = 14) or abnormal (n = 17) using holistic, conventional visual criteria including amplitude, focal differences, qualitative synchrony, and focal abnormalities. We selected 20-min epochs of discontinuous background pattern. ASI values were computed separately for different channel pair combinations and window lengths to define them for the optimal ASI intraindividual stability. Finally, ROC curves were computed to find trade-offs related to compromised data lengths, a common challenge in neonatal EEG studies. Using the average of four consecutive 2.5-min epochs in the centro-occipital bipolar derivations gave ASI estimates that very accurately distinguished babies clinically classified as normal vs. abnormal. It was even possible to draw a cut-off limit (ASI~3.6) which correctly classified the EEGs in 97% of all cases. Finally, we showed that compromising the length of EEG segments from 20 to 5 min leads to increased variability in ASI-based classification. Our findings support the prior literature that IHS is an important feature of normal neonatal brain function. We show that ASI may provide diagnostic value even at individual level, which strongly supports its use in prospective clinical studies on neonatal EEG as well as in the feature set of upcoming EEG classifiers.
Automated Discovery of Parameter Pollution Vulnerabilities in Web Applications

In the last twenty years, web applications have grown from simple, static pages to complex, full-fledged dynamic applications. Typically, these applications are built using heterogeneous technologies and consist of code that runs both on the client and on the server. Even simple web applications today may accept and process hundreds of different HTTP parameters to be able to provide users with interactive services. While injection vulnerabilities such as SQL injection and cross-site scripting are well-known and have been intensively studied by the research community, a new class of injection vulnerabilities called HTTP Parameter Pollution (HPP) has not received as much attention. If a web application does not properly sanitize the user input for parameter delimiters, exploiting an HPP vulnerability, an attacker can compromise the logic of the application to perform either client-side or server-side attacks. In this paper, we present the first automated approach for the discovery of HTTP Parameter Pollution vulnerabilities in web applications. Using our prototype implementation called PAPAS (PArameter Pollution Analysis System), we conducted a large-scale analysis of more than 5,000 popular websites. Our experimental results show that about 30% of the websites that we analyzed contain vulnerable parameters and that 46.8% of the vulnerabilities we discovered (i.e., 14% of the total websites) can be exploited via HPP attacks. The fact that PAPAS was able to find vulnerabilities in many high-profile, well-known websites suggests that many developers are not aware of the HPP problem. We informed a number of major websites about the vulnerabilities we identified, and our findings were confirmed.
Self-summarized video in adaptive collaborative e-leaming environment: Pilot study

The purpose of this research is to design an adaptive collaborative eLearning environment using Self-Summarized videos as learning media. This research aims to evaluate the outcome of the learning experience, coherence and motivation levels of the participants using user-generated summary videos tools from video lectures provided by instructors in a social and collaborative learning environment. This paper outlines the pilot study to evaluate the effectiveness of the system developed for this experiment, and to evaluate the research decisions for the full study commencing after this stage. For this research, a collaborative environment has been built where students participate in a video sharing system allowing them to create their own summarized videos and share them on the system among other participants where they can be viewed, rated and commented on. Instructors will upload the original video content. The students are allowed to use these videos to summarize video lectures in form of summarized short video clips.
Unobserved Heterogeneity in Income Dynamics: An Empirical Bayes Perspective

Empirical Bayes methods for Gaussian compound decision problems involving longitudinal data are considered. The new convex optimization formulation of the nonparametric (Kiefer–Wolfowitz) maximum likelihood estimator for mixture models is employed to construct nonparametric Bayes rules for compound decisions. The methods are first illustrated with some simulation examples and then with an application to models of income dynamics. Using panel data, we estimate a simple dynamic model of earnings that incorporates bivariate heterogeneity in intercept and variance of the innovation process. Profile likelihood is employed to estimate an AR(1) parameter controlling the persistence of the innovations. We find that persistence is relatively modest, , when we permit heterogeneity in variances. Evidence of negative dependence between individual intercepts and variances is revealed by the nonparametric estimation of the mixing distribution, and has important consequences for forecasting future income trajectories.
Effectiveness of the "Leaky Bucket" Policing Mechanism in ATM Networks

The performance of the leaky bucket, a device for controlling the source traffic parameters of an ATM network is analyzed. The most critical situation, i.e., an on/off bursty source, is assumed. Moreover, the delay jitter introduced by a possible multiplexing of sources inside the customer premises network is not considered. The leaky bucket can be analyzed as a G/D/1/N queue with finite waiting room N and a suitable arrival process. An alternative approach, the fluid flow approximation, in which the bit flow is considered as a continuous variable, is presented. By comparison with the exact model, it is shown that the accuracy of the fluid flow approach is sufficient for practical purposes. An explicit formula for the cell loss probability, in case of exponential distributions for both the burst duration and the inactivity period of the source, is derived. On the basis of that formula, some numerical evaluations are presented with the aim of assessing the effectiveness of the leaky bucket mechanism. It is concluded that while the leaky bucket can easily control the peak rate, difficulties arise in controlling the mean bit rate (because of the long time required) and the burst duration (because of the poor selectivity). >
Can Old-Age Social Insurance Be Justified?

While in America most people think of “welfare” as means-tested programs such as Aid to Families with Dependent Children, in reality in the United States and other affluent democracies the heart of the welfare state is social insurance programs, such as health insurance, old-age or retirement pensions, and unemployment insurance. They are insurance programs in the sense that they protect against common risks of a loss of income if and/or when certain events come to pass (illness, old-age or retirement, unemployment); they are “social” because unlike market insurance they are not run on a sound actuarial basis, the premiums are not voluntarily incurred but compulsory, and there is very limited choice or flexibility concerning the type of policy one can purchase. Why have social insurance rather than market insurance? In this essay, I take up this question with regard to old-age or retirement pensions, which at present absorb around 9 percent of the gross domestic product (GDP) and 25 percent of government spending of the affluent industrial countries comprising the Organization for Economic Cooperation and Development (OECD). My aim is to show that old-age or retirement social insurance (henceforth “SI”) is worse in virtually every relevant normative respect than its alternative, some form of market or private pensions. By relevant normative respect, I mean those values or principles which are used by contemporary political philosophers in their discussions and justifications of welfare-state policies, and which are applicable to assessments of different systems of old-age or retirement pensions. (Although they are applicable, almost no contemporary political philosophers have in fact applied them—an amazing state of affairs which I hope to remedy here.)