Linear stability analysis of retrieval state in associative memory neural networks of spiking neurons

We study associative memory neural networks of the Hodgkin-Huxley type of spiking neurons in which multiple periodic spatio-temporal patterns of spike timing are memorized as limit-cycle-type attractors. In encoding the spatio-temporal patterns, we assume the spike-timing-dependent synaptic plasticity with the asymmetric time window. Analysis for periodic solution of retrieval state reveals that if the area of the negative part of the time window is equivalent to the positive part, then crosstalk among encoded patterns vanishes. Phase transition due to the loss of the stability of periodic solution is observed when we assume fast alpha-function for direct interaction among neurons. In order to evaluate the critical point of this phase transition, we employ Floquet theory in which the stability problem of the infinite number of spiking neurons interacting with alpha-function is reduced into the eigenvalue problem with the finite size of matrix. Numerical integration of the single-body dynamics yields the explicit value of the matrix, which enables us to determine the critical point of the phase transition with a high degree of precision.Comment: Accepted for publication in Phys. Rev.

The Time-Energy Uncertainty Relation

The time energy uncertainty relation has been a controversial issue since the advent of quantum theory, with respect to appropriate formalisation, validity and possible meanings. A comprehensive account of the development of this subject up to the 1980s is provided by a combination of the reviews of Jammer (1974), Bauer and Mello (1978), and Busch (1990). More recent reviews are concerned with different specific aspects of the subject. The purpose of this chapter is to show that different types of time energy uncertainty relation can indeed be deduced in specific contexts, but that there is no unique universal relation that could stand on equal footing with the position-momentum uncertainty relation. To this end, we will survey the various formulations of a time energy uncertainty relation, with a brief assessment of their validity, and along the way we will indicate some new developments that emerged since the 1990s.Comment: 33 pages, Latex. This expanded version (prepared for the 2nd edition of "Time in quantum mechanics") contains minor corrections, new examples and pointers to some additional relevant literatur

A geometric approach to time evolution operators of Lie quantum systems

Lie systems in Quantum Mechanics are studied from a geometric point of view. In particular, we develop methods to obtain time evolution operators of time-dependent Schrodinger equations of Lie type and we show how these methods explain certain ad hoc methods used in previous papers in order to obtain exact solutions. Finally, several instances of time-dependent quadratic Hamiltonian are solved.Comment: Accepted for publication in the International Journal of Theoretical Physic

Choosing how to choose : Institutional pressures affecting the adoption of personnel selection procedures

The gap between science and practice in personnel selection is an ongoing concern of human resource management. This paper takes Oliver´s framework of organizations´ strategic responses to institutional pressures as a basis for outlining the diverse economic and social demands that facilitate or inhibit the application of scientifically recommended selection procedures. Faced with a complex network of multiple requirements, practitioners make more diverse choices in response to any of these pressures than has previously been acknowledged in the scientific literature. Implications for the science-practitioner gap are discussed

Learning by Teaching SimStudent: Technical Accomplishments and an Initial Use with Students

The purpose of the current study is to test whether we could create a system where students can learn by teaching a live machine-learning agent, called SimStudent. SimStudent is a computer agent that interactively learns cognitive skills through its own tutored-problem solving experience. We have developed a game-like learning environment where students learn algebra equations by tutoring SimStudent. While Simulated Students, Teachable Agents and Learning Companion systems have been created, our study is unique that it genuinely learns skills from student input. This paper describes the overview of the learning environment and some results from an evaluation study. The study showed that after tutoring SimStudent, the students improved their performance on equation solving. The number of correct answers on the error detection items was also significantly improved. On average students spent 70.0 minutes on tutoring SimStudent and used an average of 15 problems for tutoring. © Springer-Verlag Berlin Heidelberg 2010

Single-shot Ad26 vaccine protects against SARS-CoV-2 in rhesus macaques

A safe and effective vaccine for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be required to end the coronavirus disease 2019 (COVID-19) pandemic1–8. For global deployment and pandemic control, a vaccine that requires only a single immunization would be optimal. Here we show the immunogenicity and protective efficacy of a single dose of adenovirus serotype 26 (Ad26) vector-based vaccines expressing the SARS-CoV-2 spike (S) protein in non-human primates. Fifty-two rhesus macaques (Macaca mulatta) were immunized with Ad26 vectors that encoded S variants or sham control, and then challenged with SARS-CoV-2 by the intranasal and intratracheal routes9,10. The optimal Ad26 vaccine induced robust neutralizing antibody responses and provided complete or near-complete protection in bronchoalveolar lavage and nasal swabs after SARS-CoV-2 challenge. Titres of vaccine-elicited neutralizing antibodies correlated with protective efficacy, suggesting an immune correlate of protection. These data demonstrate robust single-shot vaccine protection against SARS-CoV-2 in non-human primates. The optimal Ad26 vector-based vaccine for SARS-CoV-2, termed Ad26.COV2.S, is currently being evaluated in clinical trials