Scholar iON
Academic Synthesis
The scholarly papers reviewed here focus on distinct but interconnected themes within the realm of statistical machine learning and related fields. Paulson and Griffin's work on "Minimum Probabilistic Finite State Learning Problem" delves into the complexities and solutions for learning probabilistic finite state models from finite data sets, highlighting computational challenges and approximation methods. The withdrawn papers by Sudbery and Zhu & Giannakis, although not directly contributing to the current discourse, touch upon foundational issues in quantum states and power system estimation, respectively, underscoring the evolving nature of research in these areas. Lastly, MΓΌller's exploration of dissipativity in economic model predictive control emphasizes the critical role of dissipativity conditions beyond mere steady-state optimality, reflecting a consensus on the need for more dynamic and adaptable control strategies in economic systems. Collectively, these works underscore a broader academic interest in optimizing learning and control processes across diverse applications, despite some research avenues being superseded or retracted.
This paper is withdrawn by the author. It is superseded by Makhlin's paper quant-ph/0002045.
This paper has been withdrawn by the authors
This chapter provides a concise survey on different dissipativity conditions that have appeared in the literature on economic model predictive control and discusses their decisive role in this context.
Newton's second law may be used to obtain a wave equation, which reduces to Schrodinger's equation in the nonrelativistic limit and for a conservative force.
This is a survey of the existing digital collections of French mathematical literature, run by non-profit organizations. This includes research monographs, serials, proceedings, Ph. D. theses, collected works, books and personal websites.
We demonstrate that the recently proposed pruned-enriched Rosenbluth method PERM (P.~Grassberger, Phys.~Rev.~{\bf E 56} (1997)
3682) leads to very efficient algorithms for the folding of simple model proteins. We test it on several models for lattice heteropolymers, and compare to published Monte Carlo studies of the properties of particular sequences. In all cases our method is faster than the previous ones, and in several cases we find new minimal energy states. In addition to producing more reliable candidates for ground states, our method gives detailed information about the thermal spectrum and, thus, allows to analyze static aspects of the folding behavior of arbitrary sequences.
The folding kinetics of a number of sequences for off-lattice continuum model of proteins is studied using Langevin simulations at two values of the friction coefficient. We show that there is a remarkable correlation between folding times, $Ο_{F}$, and $Ο= (T_{ΞΈ} - T_{F})/T_{ΞΈ} $, where $T_{ΞΈ}$ and $T_{F}$ are the equilibrium collapse and folding transition temperatures, respectively. The microscopic dynamics reveals several scenarios for the refolding kinetics depending on the values of $Ο$. Proteins with small $Ο$ reach the native conformation via a nucleation collapse mechanism and their energy landscape is characterized by single dominant native basin of attraction. Proteins with large $Ο$ get trapped in competing basins of attraction, in which they adopt misfolded structures. In this case only a small fraction of molecules $Ξ¦$ access the native state rapidly, the majority of them approach the native state by a three stage multipathway mechanism. The partition factor $Ξ¦$ is determined by $Ο$: smaller the value of $Ο$ larger is $Ξ¦$. The qualitative aspects of our results are found to be independent of the friction coefficient. Estimates for time scales for folding of small proteins via a nucleation collapse mechanism are presented.
This study discusses factors that keep women from entering science and technology, which include social stereotypes that they struggle against, lack of maternity leave and other basic human rights, and the climate that makes them leave research positions for administrative ones. We then describe intervention processes that have been successful in bringing the ratio of women close to parity, compare different minorities in the US, and also consider data from India, Western and Eastern Europe. We find that programs that connect the different levels of education are needed in addition to hiring more women, providing them with basic human rights from when they begin their PhD onwards and promoting support networks for existing employees. The authors of this paper hail from Sri Lanka, Romania, India, and the United States. We hold undergraduate and graduate degrees in physics or chemistry from the United States, India and Switzerland. Our conclusions are based on data that is publicly available, on data we have gathered, and on anecdotal evidence from our own experience.
Initiatives to increase the number, persistence, and success of women in physics in the US reach pre-teen girls through senior women. Programs exist at both the local and national levels. In addition, researchers have investigated issues related to gender equity in physics and physics education. Anecdotal evidence suggests increased media coverage of the underrepresentation of women in science. All of these efforts are both motivated and made more effective by the collection and presentation of data on the presence, persistence, and promise of women in physics.