515 research outputs found
Domain Walls and Metastable Vacua in Hot Orientifold Field Theories
We consider "Orientifold field theories", namely SU(N) gauge theories with
Dirac fermions in the two-index representation at high temperature. When N is
even these theories exhibit a spontaneously broken Z2 centre symmetry. We study
aspects of the domain wall that interpolates between the two vacua of the
theory. In particular we calculate its tension to two-loop order. We compare
its tension to the corresponding domain wall in a SU(N) gauge theory with
adjoint fermions and find an agreement at large-N, as expected from planar
equivalence between the two theories. Moreover, we provide a non-perturbative
proof for the coincidence of the tensions at large-N. We also discuss the
vacuum structure of the theory when the fermion is given a large mass and argue
that there exist N-2 metastable vacua. We calculate the lifetime of those vacua
in the thin wall approximation.Comment: 29 pages, 4 figures. v2: minor changes in the introduction section.
to appear in JHE
Discretized Bayesian pursuit â A new scheme for reinforcement learning
The success of Learning Automata (LA)-based estimator algorithms over the classical, Linear Reward-Inaction ( L RI )-like schemes, can be explained by their ability to pursue the actions with the highest reward probability estimates. Without access to reward probability estimates, it makes sense for schemes like the L RI to first make large exploring steps, and then to gradually turn exploration into exploitation by making progressively smaller learning steps. However, this behavior becomes counter-intuitive when pursuing actions based on their estimated reward probabilities. Learning should then ideally proceed in progressively larger steps, as the reward probability estimates turn more accurate. This paper introduces a new estimator algorithm, the Discretized Bayesian Pursuit Algorithm (DBPA), that achieves this. The DBPA is implemented by linearly discretizing the action probability space of the Bayesian Pursuit Algorithm (BPA) [1]. The key innovation is that the linear discrete updating rules mitigate the counter-intuitive behavior of the corresponding linear continuous updating rules, by augmenting them with the reward probability estimates. Extensive experimental results show the superiority of DBPA over previous estimator algorithms. Indeed, the DBPA is probably the fastest reported LA to date
Induced chromosome deletions cause hypersociability and other features of Williams-Beuren syndrome in mice
The neurodevelopmental disorder Williams-Beuren syndrome is caused by spontaneous similar to 1.5 Mb deletions comprising 25 genes on human chromosome 7q11.23. To functionally dissect the deletion and identify dosage-sensitive genes, we created two half-deletions of the conserved syntenic region on mouse chromosome 5G2. Proximal deletion (PD) mice lack Gtf2i to Limk1, distal deletion (DD) mice lack Limk1 to Fkbp6, and the double heterozygotes (D/P) model the complete human deletion. Gene transcript levels in brain are generally consistent with gene dosage. Increased sociability and acoustic startle response are associated with PD, and cognitive defects with DD. Both PD and D/P males are growth-retarded, while skulls are shortened and brains are smaller in DD and D/P. Lateral ventricle (LV) volumes are reduced, and neuronal cell density in the somatosensory cortex is increased, in PD and D/P. Motor skills are most impaired in D/P. Together, these partial deletion mice replicate crucial aspects of the human disorder and serve to identify genes and gene networks contributing to the neural substrates of complex behaviours and behavioural disorders
What can we learn from the implementation of monetary and macroprudential policies: a systematic literature review
The emergence of macroprudential policies, implemented by central banks as a means of promoting financial stability, has raised many questions regarding the interaction between monetary and macroprudential policies. Given the limited number of studies available, this paper sheds light on this issue by providing a critical and systematic review of the literature. To this end, we divide the theoretical and empirical studies into two broad channels of borrowers - consisting of the cost of funds and the collateral constraint - and financial intermediaries - consisting of risk-taking and payment systems. In spite of the existing ambiguity surrounding coordination issues between monetary and macroprudential policies, it is argued that monetary policy alone is not sufficient to maintain macroeconomic and financial stability. Hence, macroprudential policies are needed to supplement monetary. Additionally, we find that the role of the exchange rate is critical in the implementation of monetary and macroprudential policies in emerging markets, whilst volatile capital flows pose another challenge. In so far as how the arrangement of monetary and macroprudential policies varies across countries, key theoretical and policy implications have been identified
Potential conservation of circadian clock proteins in the phylum Nematoda as revealed by bioinformatic searches
Although several circadian rhythms have been described in C. elegans, its molecular clock remains elusive. In this work we employed a novel bioinformatic approach, applying probabilistic methodologies, to search for circadian clock proteins of several of the best studied circadian model organisms of different taxa (Mus musculus, Drosophila melanogaster, Neurospora crassa, Arabidopsis thaliana and Synechoccocus elongatus) in the proteomes of C. elegans and other members of the phylum Nematoda. With this approach we found that the Nematoda contain proteins most related to the core and accessory proteins of the insect and mammalian clocks, which provide new insights into the nematode clock and the evolution of the circadian system.Fil: Romanowski, AndrĂ©s. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Parque Centenario. Instituto de Investigaciones BioquĂmicas de Buenos Aires. FundaciĂłn Instituto Leloir. Instituto de Investigaciones BioquĂmicas de Buenos Aires; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y TecnologĂa. Laboratorio de CronobiologĂa; ArgentinaFil: Garavaglia, MatĂas Javier. Universidad Nacional de Quilmes. Departamento de Ciencia y TecnologĂa. Laboratorio de Ing.genĂ©tica y Biolog.molecular y Celular. Area Virus de Insectos; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Goya, MarĂa Eugenia. Universidad Nacional de Quilmes. Departamento de Ciencia y TecnologĂa. Laboratorio de CronobiologĂa; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Ghiringhelli, Pablo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y TecnologĂa. Laboratorio de Ing.genĂ©tica y Biolog.molecular y Celular. Area Virus de Insectos; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; ArgentinaFil: Golombek, Diego Andres. Universidad Nacional de Quilmes. Departamento de Ciencia y TecnologĂa. Laboratorio de CronobiologĂa; Argentina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas; Argentin
Combined quay crane assignment and quay crane scheduling with crane inter-vessel movement and non-interference constraints
Integrated models of the quay crane assignment problem (QCAP) and the quay crane scheduling problem (QCSP) exist. However, they have shortcomings in that some do not allow movement of quay cranes between vessels, others do not take into account precedence relationships between tasks, and yet others do not avoid interference between quay cranes. Here, an integrated and comprehensive optimization model that combines the two distinct QCAP and QCSP problems which deals with the issues raised is put forward. The model is of the mixed-integer programming type with the objective being to minimize the difference between tardiness cost and earliness income based on finishing time and requested departure time for a vessel. Because of the extent of the model and the potential for even small problems to lead to large instances, exact methods can be prohibitive in computational time. For this reason an adapted genetic algorithm (GA) is implemented to cope with this computational burden. Experimental results obtained with branch-and-cut as implemented in CPLEX and GA for small to large-scale problem instances are presented. The paper also includes a review of the relevant literature
Modeling a teacher in a tutorial-like system using Learning Automata
The goal of this paper is to present a novel approach to model the behavior of a Teacher in a Tutorial- like system. In this model, the Teacher is capable of presenting teaching material from a Socratic-type Domain model via multiple-choice questions. Since this knowledge is stored in the Domain model in chapters with different levels of complexity, the Teacher is able to present learning material of varying degrees of difficulty to the Students. In our model, we propose that the Teacher will be able to assist the Students to learn the more difficult material. In order to achieve this, he provides them with hints that are relative to the difficulty of the learning material presented. This enables the Students to cope with the process of handling more complex knowledge, and to be able to learn it appropriately. To our knowledge, the findings of this study are novel to the field of intelligent adaptation using Learning Automata (LA). The novelty lies in the fact that the learning system has a strategy by which it can deal with increasingly more complex/difficult Environments (or domains from which the learning as to be achieved). In our approach, the convergence of the Student models (represented by LA) is driven not only by the response of the Environment (Teacher), but also by the hints that are provided by the latter. Our proposed Teacher model has been tested against different benchmark Environments, and the results of these simulations have demonstrated the salient aspects of our model. The main conclusion is that Normal and Below-Normal learners benefited significantly from the hints provided by the Teacher, while the benefits to (brilliant) Fast learners were marginal. This seems to be in-line with our subjective understanding of the behavior of real-life Students
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