Estrogen Receptor Transrepresses Brain Inflammation

Estrogen receptors (ERs) have long been implicated in the etiology of multiple sclerosis, but no clear molecular mechanisms have linked ERs to the disease's pathology. Now Saijo et al. (2011) provide evidence that ERβ activates a transrepression pathway that suppresses inflammation and inhibits progression of pathology in a mouse model of multiple sclerosis

A Modular Voting Architecture ("Frogs")

We present a “modular voting architecture” in which “vote generation” is performed separately from “vote casting.

BlindSignedID: Mitigating Denial-of-Service Attacks on Digital Contact Tracing

Due to the recent outbreak of COVID-19, many governments suspended outdoor activities and imposed social distancing policies to prevent the transmission of SARS-CoV-2. These measures have had severe impact on the economy and peoples' daily lives. An alternative to widespread lockdowns is effective contact tracing during an outbreak's early stage. However, mathematical models suggest that epidemic control for SARS-CoV-2 transmission with manual contact tracing is implausible. To reduce the effort of contact tracing, many digital contact tracing projects (e.g., PEPP-PT, DP-3T, TCN, BlueTrace, Google/Apple Exposure Notification, and East/West Coast PACT) are being developed to supplement manual contact tracing. However, digital contact tracing has drawn scrutiny from privacy advocates, since governments or other parties may attempt to use contact tracing protocols for mass surveillance. As a result, many digital contact tracing projects build privacy-preserving mechanisms to limit the amount of privacy-sensitive information leaked by the protocol. In this paper, we examine how these architectures resist certain classes of attacks, specifically DoS attacks, and present BlindSignedIDs, a privacy-preserving digital contact tracing mechanism, which are verifiable ephemeral identifiers to limit the effectiveness of MAC-compliant DoS attacks. In our evaluations, we showed BlindSignedID can effectively deny bogus EphIDs, mitigating DoS attacks on the local storage beyond 90% of stored EphIDs. Our example DoS attacks showed that using 4 attackers can cause the gigabyte level DoS attacks within normal working hours and days.Comment: 10 pages, 6 figure

Differential geometry methods for biomedical image processing : from segmentation to 2D/3D registration

This thesis establishes a biomedical image analysis framework for the advanced visualization of biological structures. It consists of two important parts: 1) the segmentation of some structures of interest in 3D medical scans, and 2) the registration of patient-specific 3D models with 2D interventional images. Segmenting biological structures results in 3D computational models that are simple to visualize and that can be analyzed quantitatively. Registering a 3D model with interventional images permits to position the 3D model within the physical world. By combining the information from a 3D model and 2D interventional images, the proposed framework can improve the guidance of surgical intervention by reducing the ambiguities inherent to the interpretation of 2D images. Two specific segmentation problems are considered: 1) the segmentation of large structures with low frequency intensity nonuniformity, and 2) the detection of fine curvilinear structures. First, we directed our attention toward the segmentation of relatively large structures with low frequency intensity nonuniformity. Such structures are important in medical imaging since they are commonly encountered in MRI. Also, the nonuniform diffusion of the contrast agent in some other modalities, such as CTA, leads to structures of nonuniform appearance. A level-set method that uses a local-linear region model is defined, and applied to the challenging problem of segmenting brain tissues in MRI. The unique characteristics of the proposed method permit to account for important image nonuniformity implicitly. To the best of our knowledge, this is the first time a region-based level-set model has been used to perform the segmentation of real world MRI brain scans with convincing results. The second segmentation problem considered is the detection of fine curvilinear structures in 3D medical images. Detecting those structures is crucial since they can represent veins, arteries, bronchi or other important tissues. Unfortunately, most currently available curvilinear structure detection filters incur significant signal lost at bifurcations of two structures. This peculiarity limits the performance of all subsequent processes, whether it be understanding an angiography acquisition, computing an accurate tractography, or automatically classifying the image voxels. This thesis presents a new curvilinear structure detection filter that is robust to the presence of X- and Y-junctions. At the same time, it is conceptually simple and deterministic, and allows for an intuitive representation of the structure’s principal directions. Once a 3D computational model is available, it can be used to enhance surgical guidance. A 2D/3D non-rigid method is proposed that brings a 3D centerline model of the coronary arteries into correspondence with bi-plane fluoroscopic angiograms. The registered model is overlaid on top of the interventional angiograms to provide surgical assistance during image-guided chronic total occlusion procedures, which reduces the uncertainty inherent in 2D interventional images. A fully non-rigid registration model is proposed and used to compensate for any local shape discrepancy. This method is based on a variational framework, and uses a simultaneous matching and reconstruction process. With a typical run time of less than 3 seconds, the algorithms are fast enough for interactive applications

Time-space trade-offs in population protocols

Population protocols are a popular model of distributed computing, in which randomly-interacting agents with little computational power cooperate to jointly perform computational tasks. Inspired by developments in molecular computation, and in particular DNA computing, recent algorithmic work has focused on the complexity of solving simple yet fundamental tasks in the population model, such as leader election (which requires convergence to a single agent in a special "leader" state), and majority (in which agents must converge to a decision as to which of two possible initial states had higher initial count). Known results point towards an inherent trade-off between the time complexity of such algorithms, and the space complexity, i.e. size of the memory available to each agent. In this paper, we explore this trade-off and provide new upper and lower bounds for majority and leader election. First, we prove a unified lower bound, which relates the space available per node with the time complexity achievable by a protocol: for instance, our result implies that any protocol solving either of these tasks for n agents using O(log log n) states must take Ω(n/polylogn) expected time. This is the first result to characterize time complexity for protocols which employ super-constant number of states per node, and proves that fast, poly-logarithmic running times require protocols to have relatively large space costs. On the positive side, we give algorithms showing that fast, poly-logarithmic convergence time can be achieved using O(log²n) space per node, in the case of both tasks. Overall, our results highlight a time complexity separation between O (log log n) and Θ(log²n) state space size for both majority and leader election in population protocols, and introduce new techniques, which should be applicable more broadly

Time-space trade-offs in population protocols

Population protocols are a popular model of distributed computing, in which randomly-interacting agents with little computational power cooperate to jointly perform computational tasks. Inspired by developments in molecular computation, and in particular DNA computing, recent algorithmic work has focused on the complexity of solving simple yet fundamental tasks in the population model, such as leader election (which requires convergence to a single agent in a special "leader" state), and majority (in which agents must converge to a decision as to which of two possible initial states had higher initial count). Known results point towards an inherent trade-off between the time complexity of such algorithms, and the space complexity, i.e. size of the memory available to each agent. In this paper, we explore this trade-off and provide new upper and lower bounds for majority and leader election. First, we prove a unified lower bound, which relates the space available per node with the time complexity achievable by a protocol: for instance, our result implies that any protocol solving either of these tasks for n agents using O(log log n) states must take Ω(n/polylogn) expected time. This is the first result to characterize time complexity for protocols which employ super-constant number of states per node, and proves that fast, poly-logarithmic running times require protocols to have relatively large space costs. On the positive side, we give algorithms showing that fast, poly-logarithmic convergence time can be achieved using O(log²n) space per node, in the case of both tasks. Overall, our results highlight a time complexity separation between O (log log n) and Θ(log²n) state space size for both majority and leader election in population protocols, and introduce new techniques, which should be applicable more broadly

07311 Abstracts Collection -- Frontiers of Electronic Voting

From July the 29th to August the 3th, 2007, the Dagstuhl Seminar 07311 ``Frontiers of Electronic Voting\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Construing Worst Experiences of the COVID-19 Pandemic in the USA: A Thematic Analysis

© 2022 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/.The COVID-19 pandemic has not only resulted in millions of deaths but, together with the strategies imposed to contain the spread of the disease, it has had significant psychological and social effects. This paper considers these effects in residents of the USA, the country that has reported the highest number of deaths from COVID-19. Between April and May, 2020, responses were obtained to an on-line survey, which included asking participants, recruited by snowball sampling, to describe their worst experience of the pandemic. The responses of 741 participants, primarily female and Caucasian, were subjected to a thematic content analysis which used a primarily deductive approach in which these responses were viewed in terms of transitions in construing. The transition themes identified were anxiety; threat; loss of role; sadness; contempt; and stress. Various subthemes were also identified. The study provided further evidence of the utility of a personal construct framework in conceptualizing experiences associated with illness and the risk of this. Implications of its findings are considered at both an individual and a societal level.Peer reviewedFinal Published versio

Experiences from southern Quebec provide ecological insights for the implementation of tree-based intercropping systems

Paper presented at the 11th North American Agroforesty Conference, which was held May 31-June 3, 2009 in Columbia, Missouri.In Gold, M.A. and M.M. Hall, eds. Agroforestry Comes of Age: Putting Science into Practice. Proceedings, 11th North American Agroforestry Conference, Columbia, Mo., May 31-June 3, 2009.Recent experiments in Quebec aimed to provide scientific arguments favouring the adoption of tree-based intercropping (TBI) systems in eastern Canada's rural landscape. The specific objectives of this research were to: (1) test whether a soybean intercrop between tree rows increases soil microbial biomass C, soil N fertility and tree growth compared to a harrowing treatment between tree rows; (2) determine the effects of the soybean intercrop on the diversity of arbuscular mycorrhizal fungi (assessed using SSU rRNA genes) compared to harrowing; and (3) determine whether TBI increases soil microbial beta-diversity (assessed using extractable phospholipid fatty acid (PLFA) profiles) compared to an adjacent conventional monocropping system. The TBI field was set in 2000 in southwestern Quebec using alternating rows of hybrid poplars (Populus spp.) and hardwood species spaced 8 m apart. Soybean (Glycine max L. (Merr.)) was grown between tree rows since 2004. During the 2005-2006 study period, soil microbial biomass C and N availability were higher in the soybean intercrop treatment or on par with those in the harrowing treatment. Hybrid poplar biomass increment in the soybean intercrop treatment was greater by 51 [percent] to that in the harrowing treatment and diagnostic of leaf nutrient status indicated that hybrid poplars were positively affected by the increase in N supply provided through intercrop management. The arbuscular mycorrhizal fungal diversity, as expressed by the Shannon-Wiener indices, were 0.82 for the soybean and 0.70 for hybrid poplar under the soybean intercrop treatment, and 0.53 for hybrid poplar under the harrowing treatment. The neighboring trees and soybean plants hosted different arbuscular mycorrhizal fungal communities, suggesting that TBI systems may enhance arbuscular mycorrhizal fungal richness compared to monocultures. The soil microbial beta-diversity, based on a measure of dispersion among the PLFA profiles within each sampled grid, was higher in the TBI than in the conventional soybean monocropping system, suggesting that TBI systems could play an important ecological role in the conservation of microbial functions (e.g., nutrient cycling), even in the face of wide variations of environmental conditions and inputs.David Rivest (1), Vincent Chifflot (2), Simon Lacombe (3), Alain Cogliastro (4), Robert Bradley (3), Anne Vanasse (1), Damase Khasa (2) and Alain Olivier (1) ; 1. De_partement de phytologie, Universit� Laval, Qu�bec (QC), Canada. 2. D�partement des sciences du bois et de la for�t, Universit� Laval, Qu�bec (QC), Canada. 3. D�partement de biologie, Universit� de Sherbrooke, Sherbrooke (QC), Canada. 4. Institut de recherche en biologie v�g�tale, Universit� de Montr�al & Jardin botanique de Montr�al, Montr�al (QC), Canada.n and 0.70 forIncludes bibliographical references

Micropayments for Decentralized Currencies

Electronic financial transactions in the US, even those enabled by Bitcoin, have relatively high transaction costs. As a result, it becomes infeasible to make \emph{micropayments}, i.e. payments that are pennies or fractions of a penny. To circumvent the cost of recording all transactions, Wheeler (1996) and Rivest (1997) suggested the notion of a \emph{probabilistic payment}, that is, one implements payments that have \emph{expected} value on the order of micro pennies by running an appropriately biased lottery for a larger payment. While there have been quite a few proposed solutions to such lottery-based micropayment schemes, all these solutions rely on a trusted third party to coordinate the transactions; furthermore, to implement these systems in today\u27s economy would require a a global change to how either banks or electronic payment companies (e.g., Visa and Mastercard) handle transactions. We put forth a new lottery-based micropayment scheme for any ledger-based transaction system, that can be used today without any change to the current infrastructure. We implement our scheme in a sample web application and show how a single server can handle thousands of micropayment requests per second. We analyze how the scheme can work at Internet scale