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

An ORMOSIL-containing orthodontic acrylic resin with concomitant improvements in antimicrobial and fracture toughness properties

Global increase in patients seeking orthodontic treatment creates a demand for the use of acrylic resins in removable appliances and retainers. Orthodontic removable appliance wearers have a higher risk of oral infections that are caused by the formation of bacterial and fungal biofilms on the appliance surface. Here, we present the synthetic route for an antibacterial and antifungal organically-modified silicate (ORMOSIL) that has multiple methacryloloxy functionalities attached to a siloxane backbone (quaternary ammonium methacryloxy silicate, or QAMS). By dissolving the water-insoluble, rubbery ORMOSIL in methyl methacrylate, QAMS may be copolymerized with polymethyl methacrylate, and covalently incorporated in the pressure-processed acrylic resin. The latter demonstrated a predominantly contact-killing effect on Streptococcus mutans ATCC 36558 and Actinomyces naselundii ATCC 12104 biofilms, while inhibiting adhesion of Candida albicans ATCC 90028 on the acrylic surface. Apart from its favorable antimicrobial activities, QAMS-containing acrylic resins exhibited decreased water wettability and improved toughness, without adversely affecting the flexural strength and modulus, water sorption and solubility, when compared with QAMS-free acrylic resin. The covalently bound, antimicrobial orthodontic acrylic resin with improved toughness represents advancement over other experimental antimicrobial acrylic resin formulations, in its potential to simultaneously prevent oral infections during appliance wear, and improve the fracture resistance of those appliances.published_or_final_versio

Experimental Research on the Shear Connectors in Foam Concrete

In order to improve the longitudinal shear resistance between foam concrete and C-Channels, an investigation is carried out on the shear connectors in foam concrete with cold-formed steel double C-Channels embedment. Twenty-four tests have been carried out in two groups. Two types of connectors: flange connectors and web connectors are installed using self-drilling screws for a rapid construction. The experimental results show that they can effectively improve the longitudinal shear-resist capacity of the concrete. After the experiment, the specimens are dismantled for an interior observation. Based on the observation, the form of damage, the failure mechanism was discovered, and the equation of longitudinal shear capacity was developed. It is concluded that the failure involves independent slippage between two C-Channels and the shear connection fractures. Since the composite structure requires sufficient slip between the two materials, these types of shear connectors will have good enhancement for this type of composite structures subjected to dynamic loads

Blockade of insulin-like growth factors increases efficacy of paclitaxel in metastatic breast cancer.

Breast cancer remains the leading cause of cancer death in women owing to metastasis and the development of resistance to established therapies. Macrophages are the most abundant immune cells in the breast tumor microenvironment and can both inhibit and support cancer progression. Thus, gaining a better understanding of how macrophages support cancer could lead to the development of more effective therapies. In this study, we find that breast cancer-associated macrophages express high levels of insulin-like growth factors 1 and 2 (IGFs) and are the main source of IGFs within both primary and metastatic tumors. In total, 75% of breast cancer patients show activation of insulin/IGF-1 receptor signaling and this correlates with increased macrophage infiltration and advanced tumor stage. In patients with invasive breast cancer, activation of Insulin/IGF-1 receptors increased to 87%. Blocking IGF in combination with paclitaxel, a chemotherapeutic agent commonly used to treat breast cancer, showed a significant reduction in tumor cell proliferation and lung metastasis in pre-clinical breast cancer models compared to paclitaxel monotherapy. Our findings provide the rationale for further developing the combination of paclitaxel with IGF blockers for the treatment of invasive breast cancer, and Insulin/IGF1R activation and IGF+ stroma cells as potential biomarker candidates for further evaluation

Occlusion of Regulatory Sequences by Promoter Nucleosomes In Vivo

Nucleosomes are believed to inhibit DNA binding by transcription factors. Theoretical attempts to understand the significance of nucleosomes in gene expression and regulation are based upon this assumption. However, nucleosomal inhibition of transcription factor binding to DNA is not complete. Rather, access to nucleosomal DNA depends on a number of factors, including the stereochemistry of transcription factor-DNA interaction, the in vivo kinetics of thermal fluctuations in nucleosome structure, and the intracellular concentration of the transcription factor. In vitro binding studies must therefore be complemented with in vivo measurements. The inducible PHO5 promoter of yeast has played a prominent role in this discussion. It bears two binding sites for the transcriptional activator Pho4, which at the repressed promoter are positioned within a nucleosome and in the linker region between two nucleosomes, respectively. Earlier studies suggested that the nucleosomal binding site is inaccessible to Pho4 binding in the absence of chromatin remodeling. However, this notion has been challenged by several recent reports. We therefore have reanalyzed transcription factor binding to the PHO5 promoter in vivo, using ‘chromatin endogenous cleavage’ (ChEC). Our results unambiguously demonstrate that nucleosomes effectively interfere with the binding of Pho4 and other critical transcription factors to regulatory sequences of the PHO5 promoter. Our data furthermore suggest that Pho4 recruits the TATA box binding protein to the PHO5 promoter

Learning deterministic probabilistic automata from a model checking perspective

Probabilistic automata models play an important role in the formal design and analysis of hard- and software systems. In this area of applications, one is often interested in formal model-checking procedures for verifying critical system properties. Since adequate system models are often difficult to design manually, we are interested in learning models from observed system behaviors. To this end we adopt techniques for learning finite probabilistic automata, notably the Alergia algorithm. In this paper we show how to extend the basic algorithm to also learn automata models for both reactive and timed systems. A key question of our investigation is to what extent one can expect a learned model to be a good approximation for the kind of probabilistic properties one wants to verify by model checking. We establish theoretical convergence properties for the learning algorithm as well as for probability estimates of system properties expressed in linear time temporal logic and linear continuous stochastic logic. We empirically compare the learning algorithm with statistical model checking and demonstrate the feasibility of the approach for practical system verification

HIT family genes: FHIT but not PKCI-1/HINT produces altered transcripts in colorectal cancer

Forty-five colorectal adenocarcinomas were examined for alterations in the HIT family genes FHIT and PKCI-1/HINT by a combination of reverse transcriptase polymerase chain reaction and DNA sequencing. In all cases a single transcript corresponding to the reported sequence was detected using primers specific for the PKCI-1/HINT gene. In contrast multiple transcripts were detected using primers specific for the FHIT gene transcript. 6% (3/45) of tumours evinced no detectable expression of any FHIT transcript and a further 12% (6/45) produced only the normal full length transcripts. Ninety-six aberrant transcripts were characterized from the remaining tumours. Deviations from the normal full length sequence characterized included deletions, insertions of novel sequences, a point mutation as well as the usage of a putative alternate splice site in exon 10. Message variants were detected with approximately equal frequency in all tumour stages with the exception that templates with insertions were found solely in Dukes’ stage B tumours (P < 0.001). With the exception of the putative alternate splice site, aberrant transcripts were not detected in matched normal mucosa. These results suggest that members of the HIT family of genes are only selectively involved in tumorigenesis and that perturbation of FHIT gene expression is an early event in colorectal tumorigenesis. © 1999 Cancer Research Campaig

Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay

The decay channel $\psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p})$ is studied using a sample of $1.06\times 10^8$ $\psi^\prime$ events collected by the BESIII experiment at BEPCII. A strong enhancement at threshold is observed in the $p\bar{p}$ invariant mass spectrum. The enhancement can be fit with an $S$-wave Breit-Wigner resonance function with a resulting peak mass of $M=1861^{+6}_{-13} {\rm (stat)}^{+7}_{-26} {\rm (syst)} {\rm MeV/}c^2$ and a narrow width that is $\Gamma<38 {\rm MeV/}c^2$ at the 90% confidence level. These results are consistent with published BESII results. These mass and width values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

Measurement of the t(t)over-bar production cross section in the dilepton channel in pp collisions at √s=8 TeV

The top-antitop quark (t (t) over bar) production cross section is measured in proton-proton collisions at root s = 8 TeV with the CMS experiment at the LHC, using a data sample corresponding to an integrated luminosity of 5.3 fb(-1). The measurement is performed by analysing events with a pair of electrons or muons, or one electron and one muon, and at least two jets, one of which is identified as originating from hadronisation of a bottom quark. The measured cross section is 239 +/- 2 (stat.) +/- 11 (syst.) +/- 6 (lum.) pb, for an assumed top-quark mass of 172.5 GeV, in agreement with the prediction of the standard model