Université de Montréal

About: Université de Montréal is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 45641 authors who have published 100476 publications receiving 4004007 citations. The organization is also known as: University of Montreal & UdeM.

Unconditionally Secure Quantum Bit Commitment is Impossible

Abstract: The claim of quantum cryptography has always been that it can provide protocols that are unconditionally secure, that is, for which the security does not depend on any restriction on the time, space, or technology available to the cheaters. We show that this claim does not hold for any quantum bit commitment protocol. Since many cryptographic tasks use bit commitment as a basic primitive, this result implies a severe setback for quantum cryptography. The model used encompasses all reasonable implementations of quantum bit commitment protocols in which the participants have not met before, including those that make use of the theory of special relativity.

Impairing follicle-stimulating hormone (FSH) signaling in vivo: Targeted disruption of the FSH receptor leads to aberrant gametogenesis and hormonal imbalance

Abstract: Pituitary gonadotropins follicle-stimulating hormone (FSH) and luteinizing hormone stimulate the gonads by regulating germ cell proliferation and differentiation. FSH receptors (FSH-Rs) are localized to testicular Sertoli cells and ovarian granulosa cells and are coupled to activation of the adenylyl cyclase and other signaling pathways. Activation of FSH-Rs is considered essential for folliculogenesis in the female and spermatogenesis in the male. We have generated mice lacking FSH-R by homologous recombination. FSH-R-deficient males are fertile but display small testes and partial spermatogenic failure. Thus, although FSH signaling is not essential for initiating spermatogenesis, it appears to be required for adequate viability and motility of the sperms. FSH-R-deficient females display thin uteri and small ovaries and are sterile because of a block in folliculogenesis before antral follicle formation. Although the expression of marker genes is only moderately altered in FSH-R −/− mice, drastic sex-specific changes are observed in the levels of various hormones. The anterior lobe of the pituitary gland in females is enlarged and reveals a larger number of FSH- and thyroid-stimulating hormone (TSH)-positive cells. The phenotype of FSH-R −/− mice is reminiscent of human hypergonadotropic ovarian dysgenesis and infertility.

Smart card data use in public transit: A literature review

Abstract: Smart card automated fare collection systems are being used more and more by public transit agencies. While their main purpose is to collect revenue, they also produce large quantities of very detailed data on onboard transactions. These data can be very useful to transit planners, from the day-to-day operation of the transit system to the strategic long-term planning of the network. This review covers several aspects of smart card data use in the public transit context. First, the technologies are presented: the hardware and information systems required to operate these tools; and privacy concerns and legal issues related to the dissemination of smart card data, data storage, and encryption are addressed. Then, the various uses of the data at three levels of management are described: strategic (long-term planning), tactical (service adjustments and network development), and operational (ridership statistics and performance indicators). Also reported are smart card commercialization experiments conducted all over the world. Finally, the most promising research avenues for smart card data in this field are presented; for example, comparison of planned and implemented schedules, systematic schedule adjustments, and the survival models applied to ridership.

Personalizing Dialogue Agents: I have a dog, do you have pets too?

Abstract: Chit-chat models are known to have several problems: they lack specificity, do not display a consistent personality and are often not very captivating. In this work we present the task of making chit-chat more engaging by conditioning on profile information. We collect data and train models to (i)condition on their given profile information; and (ii) information about the person they are talking to, resulting in improved dialogues, as measured by next utterance prediction. Since (ii) is initially unknown our model is trained to engage its partner with personal topics, and we show the resulting dialogue can be used to predict profile information about the interlocutors.