Introducing a framework to assess newly created questions with Natural Language Processing

Statistical models such as those derived from Item Response Theory (IRT) enable the assessment of students on a specific subject, which can be useful for several purposes (e.g., learning path customization, drop-out prediction). However, the questions have to be assessed as well and, although it is possible to estimate with IRT the characteristics of questions that have already been answered by several students, this technique cannot be used on newly generated questions. In this paper, we propose a framework to train and evaluate models for estimating the difficulty and discrimination of newly created Multiple Choice Questions by extracting meaningful features from the text of the question and of the possible choices. We implement one model using this framework and test it on a real-world dataset provided by CloudAcademy, showing that it outperforms previously proposed models, reducing by 6.7% the RMSE for difficulty estimation and by 10.8% the RMSE for discrimination estimation. We also present the results of an ablation study performed to support our features choice and to show the effects of different characteristics of the questions' text on difficulty and discrimination.Comment: Accepted at the International Conference of Artificial Intelligence in Educatio

Treating symptomatic uterine fibroids with myomectomy: current practice and views of UK consultants

Background: The demand for uterus-sparing treatments is increasing as more women postpone childbirth to their 30–40s, when fibroids are more symptomatic. With an increasing choice of treatment options and changing care-provider profiles, now is an opportune time to survey current practices and opinions. Using a 25-stem questionnaire, a web-based survey was used to capture the practices and opinions of UK consultant gynecologists on the treatment of symptomatic fibroids, including the types of procedure most frequently used, methods used to reduce blood loss, and awareness and acceptability of treatment options, and to assess the impact of gender and experience of the treating gynecologist. Results: The response rate was 22%. Laparascopic myomectomy is used least frequently, with 80% of the respondents using GnRHa preoperatively to minimize blood loss and correct anemia, while vasopressin is most frequently used to reduce intraoperative blood loss. Female consultants operate significantly less frequently than males. Those with more than 10 years consultant experience are more likely to perform an open myomectomy compared to those with less than 10 years experience. Conclusions: Compared to a similar survey performed 10 years ago, surgical methods remain to be the most common treatments, but use of less invasive treatments such as UAE has increased. Consultants’ attitudes appear to be responding to the patient demand for less radical treatments. However, it is yet to be seen if the changing consultant demographics will keep up with this demand. The low response rate warrants cautious interpretation of the results, but they provide an interesting snapshot of current views and practices

A fast and flexible panoramic virtual reality system for behavioural and electrophysiological experiments

Ideally, neuronal functions would be studied by performing experiments with unconstrained animals whilst they behave in their natural environment. Although this is not feasible currently for most animal models, one can mimic the natural environment in the laboratory by using a virtual reality (VR) environment. Here we present a novel VR system based upon a spherical projection of computer generated images using a modified commercial data projector with an add-on fish-eye lens. This system provides equidistant visual stimulation with extensive coverage of the visual field, high spatio-temporal resolution and flexible stimulus generation using a standard computer. It also includes a track-ball system for closed-loop behavioural experiments with walking animals. We present a detailed description of the system and characterize it thoroughly. Finally, we demonstrate the VR system’s performance whilst operating in closed-loop conditions by showing the movement trajectories of the cockroaches during exploratory behaviour in a VR forest

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Activation of Latent HIV Using Drug-Loaded Nanoparticles

Antiretroviral therapy is currently only capable of controlling HIV replication rather than completely eradicating virus from patients. This is due in part to the establishment of a latent virus reservoir in resting CD4+ T cells, which persists even in the presence of HAART. It is thought that forced activation of latently infected cells could induce virus production, allowing targeting of the cell by the immune response. A variety of molecules are able to stimulate HIV from latency. However no tested purging strategy has proven capable of eliminating the infection completely or preventing viral rebound if therapy is stopped. Hence novel latency activation approaches are required. Nanoparticles can offer several advantages over more traditional drug delivery methods, including improved drug solubility, stability, and the ability to simultaneously target multiple different molecules to particular cell or tissue types. Here we describe the development of a novel lipid nanoparticle with the protein kinase C activator bryostatin-2 incorporated (LNP-Bry). These particles can target and activate primary human CD4+ T-cells and stimulate latent virus production from human T-cell lines in vitro and from latently infected cells in a humanized mouse model ex vivo. This activation was synergistically enhanced by the HDAC inhibitor sodium butyrate. Furthermore, LNP-Bry can also be loaded with the protease inhibitor nelfinavir (LNP-Bry-Nel), producing a particle capable of both activating latent virus and inhibiting viral spread. Taken together these data demonstrate the ability of nanotechnological approaches to provide improved methods for activating latent HIV and provide key proof-of-principle experiments showing how novel delivery systems may enhance future HIV therapy

Assessing learning and memory in pigs

In recent years, there has been a surge of interest in (mini) pigs (Sus scrofa) as species for cognitive research. A major reason for this is their physiological and anatomical similarity with humans. For example, pigs possess a well-developed, large brain. Assessment of the learning and memory functions of pigs is not only relevant to human research but also to animal welfare, given the nature of current farming practices and the demands they make on animal health and behavior. In this article, we review studies of pig cognition, focusing on the underlying processes and mechanisms, with a view to identifying. Our goal is to aid the selection of appropriate cognitive tasks for research into pig cognition. To this end, we formulated several basic criteria for pig cognition tests and then applied these criteria and knowledge about pig-specific sensorimotor abilities and behavior to evaluate the merits, drawbacks, and limitations of the different types of tests used to date. While behavioral studies using (mini) pigs have shown that this species can perform learning and memory tasks, and much has been learned about pig cognition, results have not been replicated or proven replicable because of the lack of validated, translational behavioral paradigms that are specially suited to tap specific aspects of pig cognition. We identified several promising types of tasks for use in studies of pig cognition, such as versatile spatial free-choice type tasks that allow the simultaneous measurement of several behavioral domains. The use of appropriate tasks will facilitate the collection of reliable and valid data on pig cognition

Planetary Rings

Planetary rings are the only nearby astrophysical disks, and the only disks that have been investigated by spacecraft. Although there are significant differences between rings and other disks, chiefly the large planet/ring mass ratio that greatly enhances the flatness of rings (aspect ratios as small as 1e-7), understanding of disks in general can be enhanced by understanding the dynamical processes observed at close-range and in real-time in planetary rings. We review the known ring systems of the four giant planets, as well as the prospects for ring systems yet to be discovered. We then review planetary rings by type. The main rings of Saturn comprise our system's only dense broad disk and host many phenomena of general application to disks including spiral waves, gap formation, self-gravity wakes, viscous overstability and normal modes, impact clouds, and orbital evolution of embedded moons. Dense narrow rings are the primary natural laboratory for understanding shepherding and self-stability. Narrow dusty rings, likely generated by embedded source bodies, are surprisingly found to sport azimuthally-confined arcs. Finally, every known ring system includes a substantial component of diffuse dusty rings. Planetary rings have shown themselves to be useful as detectors of planetary processes around them, including the planetary magnetic field and interplanetary impactors as well as the gravity of nearby perturbing moons. Experimental rings science has made great progress in recent decades, especially numerical simulations of self-gravity wakes and other processes but also laboratory investigations of coefficient of restitution and spectroscopic ground truth. The age of self-sustained ring systems is a matter of debate; formation scenarios are most plausible in the context of the early solar system, while signs of youthfulness indicate at least that rings have never been static phenomena.Comment: 82 pages, 34 figures. Final revision of general review to be published in "Planets, Stars and Stellar Systems", P. Kalas and L. French (eds.), Springer (http://refworks.springer.com/sss

An Antagomir to MicroRNA Let7f Promotes Neuroprotection in an Ischemic Stroke Model

We previously showed that middle-aged female rats sustain a larger infarct following experimental stroke as compared to younger female rats, and paradoxically, estrogen treatment to the older group is neurotoxic. Plasma and brain insulin-like growth factor-1 (IGF-1) levels decrease with age. However, IGF-1 infusion following stroke, prevents estrogen neurotoxicity in middle-aged female rats. IGF1 is neuroprotective and well tolerated, but also has potentially undesirable side effects. We hypothesized that microRNAs (miRNAs) that target the IGF-1 signaling family for translation repression could be alternatively suppressed to promote IGF-1-like neuroprotection. Here, we report that two conserved IGF pathway regulatory microRNAs, Let7f and miR1, can be inhibited to mimic and even extend the neuroprotection afforded by IGF-1. Anti-mir1 treatment, as late as 4 hours following ischemia, significantly reduced cortical infarct volume in adult female rats, while anti-Let7 robustly reduced both cortical and striatal infarcts, and preserved sensorimotor function and interhemispheric neural integration. No neuroprotection was observed in animals treated with a brain specific miRNA unrelated to IGF-1 (anti-miR124). Remarkably, anti-Let7f was only effective in intact females but not males or ovariectomized females indicating that the gonadal steroid environment critically modifies miRNA action. Let7f is preferentially expressed in microglia in the ischemic hemisphere and confirmed in ex vivo cultures of microglia obtained from the cortex. While IGF-1 was undetectable in microglia harvested from the non-ischemic hemisphere, IGF-1 was expressed by microglia obtained from the ischemic cortex and was further elevated by anti-Let7f treatment. Collectively these data support a novel miRNA-based therapeutic strategy for neuroprotection following stroke

Neocortical Axon Arbors Trade-off Material and Conduction Delay Conservation

The brain contains a complex network of axons rapidly communicating information between billions of synaptically connected neurons. The morphology of individual axons, therefore, defines the course of information flow within the brain. More than a century ago, Ramón y Cajal proposed that conservation laws to save material (wire) length and limit conduction delay regulate the design of individual axon arbors in cerebral cortex. Yet the spatial and temporal communication costs of single neocortical axons remain undefined. Here, using reconstructions of in vivo labelled excitatory spiny cell and inhibitory basket cell intracortical axons combined with a variety of graph optimization algorithms, we empirically investigated Cajal's conservation laws in cerebral cortex for whole three-dimensional (3D) axon arbors, to our knowledge the first study of its kind. We found intracortical axons were significantly longer than optimal. The temporal cost of cortical axons was also suboptimal though far superior to wire-minimized arbors. We discovered that cortical axon branching appears to promote a low temporal dispersion of axonal latencies and a tight relationship between cortical distance and axonal latency. In addition, inhibitory basket cell axonal latencies may occur within a much narrower temporal window than excitatory spiny cell axons, which may help boost signal detection. Thus, to optimize neuronal network communication we find that a modest excess of axonal wire is traded-off to enhance arbor temporal economy and precision. Our results offer insight into the principles of brain organization and communication in and development of grey matter, where temporal precision is a crucial prerequisite for coincidence detection, synchronization and rapid network oscillations

Special cases : moons, rings, comets, trojans

Non-planetary bodies provide valuable insight into our current under- standing of planetary formation and evolution. Although these objects are challeng- ing to detect and characterize, the potential information to be drawn from them has motivated various searches through a number of techniques. Here, we briefly review the current status in the search of moons, rings, comets, and trojans in exoplanet systems and suggest what future discoveries may occur in the near future.Comment: Invited review (status August 2017