Asymptotic Level Density of the Elastic Net Self-Organizing Feature Map

Whileas the Kohonen Self Organizing Map shows an asymptotic level density following a power law with a magnification exponent 2/3, it would be desired to have an exponent 1 in order to provide optimal mapping in the sense of information theory. In this paper, we study analytically and numerically the magnification behaviour of the Elastic Net algorithm as a model for self-organizing feature maps. In contrast to the Kohonen map the Elastic Net shows no power law, but for onedimensional maps nevertheless the density follows an universal magnification law, i.e. depends on the local stimulus density only and is independent on position and decouples from the stimulus density at other positions.Comment: 8 pages, 10 figures. Link to publisher under http://link.springer.de/link/service/series/0558/bibs/2415/24150939.ht

A New Simulated Annealing Algorithm for the Multiple Sequence Alignment Problem: The approach of Polymers in a Random Media

We proposed a probabilistic algorithm to solve the Multiple Sequence Alignment problem. The algorithm is a Simulated Annealing (SA) that exploits the representation of the Multiple Alignment between $D$ sequences as a directed polymer in $D$ dimensions. Within this representation we can easily track the evolution in the configuration space of the alignment through local moves of low computational cost. At variance with other probabilistic algorithms proposed to solve this problem, our approach allows for the creation and deletion of gaps without extra computational cost. The algorithm was tested aligning proteins from the kinases family. When D=3 the results are consistent with those obtained using a complete algorithm. For $D>3$ where the complete algorithm fails, we show that our algorithm still converges to reasonable alignments. Moreover, we study the space of solutions obtained and show that depending on the number of sequences aligned the solutions are organized in different ways, suggesting a possible source of errors for progressive algorithms.Comment: 7 pages and 11 figure

On the Disambiguation of Weighted Automata

We present a disambiguation algorithm for weighted automata. The algorithm admits two main stages: a pre-disambiguation stage followed by a transition removal stage. We give a detailed description of the algorithm and the proof of its correctness. The algorithm is not applicable to all weighted automata but we prove sufficient conditions for its applicability in the case of the tropical semiring by introducing the *weak twins property*. In particular, the algorithm can be used with all acyclic weighted automata, relevant to applications. While disambiguation can sometimes be achieved using determinization, our disambiguation algorithm in some cases can return a result that is exponentially smaller than any equivalent deterministic automaton. We also present some empirical evidence of the space benefits of disambiguation over determinization in speech recognition and machine translation applications

Addition-Deletion Networks

We study structural properties of growing networks where both addition and deletion of nodes are possible. Our model network evolves via two independent processes. With rate r, a node is added to the system and this node links to a randomly selected existing node. With rate 1, a randomly selected node is deleted, and its parent node inherits the links of its immediate descendants. We show that the in-component size distribution decays algebraically, c_k ~ k^{-beta}, as k-->infty. The exponent beta=2+1/(r-1) varies continuously with the addition rate r. Structural properties of the network including the height distribution, the diameter of the network, the average distance between two nodes, and the fraction of dangling nodes are also obtained analytically. Interestingly, the deletion process leads to a giant hub, a single node with a macroscopic degree whereas all other nodes have a microscopic degree.Comment: 8 pages, 5 figure

Female Faculty: Why So Few and Why Care?

Despite slow ongoing progress in increasing the representation of women in academia, women remain significantly under-represented at senior levels, in particular in the natural sciences and engineering. Not infrequently, this is downplayed by bringing forth arguments such as inherent biological differences between genders, that current policies are adequate to address the issue, or by deflecting this as being “not my problem” among other examples. In this piece we present scientific evidence that counters these claims, as well as a best-practice example, Genie, from Chalmers University of Technology, where one of the authors is currently employed. We also highlight particular challenges caused by the current COVID-19 pandemic. Finally, we conclude by proposing some possible solutions to the situation and emphasize that we need to all do our part, to ensure that the next generation of academics experience a more diverse, inclusive, and equitable working environment

Clinical and molecular correlates in fragile X premutation females.

The prevalence of the fragile X premutation (55-200 CGG repeats) among the general population is relatively high, but there remains a lack of clear understanding of the links between molecular biomarkers and clinical outcomes. In this study we investigated the correlations between molecular measures (CGG repeat size, FMR1 mRNA, FMRP expression levels, and methylation status at the promoter region and in FREE2 site) and clinical phenotypes (anxiety, obsessive compulsive symptoms, depression and executive function deficits) in 36 adult premutation female carriers and compared to 24 normal control subjects. Premutation carriers reported higher levels of obsessive compulsive symptoms, depression, and anxiety, but demonstrated no significant deficits in global cognitive functions or executive function compared to the control group. Increased age in carriers was significantly associated with increased anxiety levels. As expected, FMR1 mRNA expression was significantly correlated with CGG repeat number. However, no significant correlations were observed between molecular (including epigenetic) measures and clinical phenotypes in this sample. Our study, albeit limited by the sample size, establishes the complexity of the mechanisms that link the FMR1 locus to the clinical phenotypes commonly observed in female carriers suggesting that other factors, including environment or additional genetic changes, may have an impact on the clinical phenotypes. However, it continues to emphasize the need for assessment and treatment of psychiatric problems in female premutation carriers

Reorientation of Spin Density Waves in Cr(001) Films induced by Fe(001) Cap Layers

Proximity effects of 20 \AA thin Fe layers on the spin density waves (SDWs) in epitaxial Cr(001) films are revealed by neutron scattering. Unlike in bulk Cr we observe a SDW with its wave vector Q pointing along only one {100} direction which depends dramatically on the film thickness t_{Cr}. For t_{Cr} < 250 \AA the SDW propagates out-of-plane with the spins in the film plane. For t_{Cr} > 1000 \AA the SDW propagates in the film plane with the spins out-of-plane perpendicular to the in-plane Fe moments. This reorientation transition is explained by frustration effects in the antiferromagnetic interaction between Fe and Cr across the Fe/Cr interface due to steps at the interface.Comment: 4 pages (RevTeX), 3 figures (EPS