Transverse laser cooling of a thermal atomic beam of dysprosium

A thermal atomic beam of dysprosium (Dy) atoms is cooled using the $4f^{10}6s^2 (J=8) \to 4f^{10}6s6p (J=9)$ transition at 421 nm. The cooling is done via a standing light wave orthogonal to the atomic beam. Efficient transverse cooling to the Doppler limit is demonstrated for all observable isotopes of dysprosium. Branching ratios to metastable states are demonstrated to be $<5\times10^{-4}$. A scheme for enhancement of the nonzero-nuclear-spin-isotope cooling, as well as a method for direct identification of possible trap states, is proposed.Comment: 5 pages, 4 figures v2: 7 pages, 7 figure

Autoregulation in resistance training : addressing the inconsistencies

Autoregulation is a process that is used to manipulate training based primarily on the measurement of an individual's performance or their perceived capability to perform. Despite being established as a training framework since the 1940s, there has been limited systematic research investigating its broad utility. Instead, researchers have focused on disparate practices that can be considered specific examples of the broader autoregulation training framework. A primary limitation of previous research includes inconsistent use of key terminology (e.g., adaptation, readiness, fatigue, and response) and associated ambiguity of how to implement different autoregulation strategies. Crucially, this ambiguity in terminology and failure to provide a holistic overview of autoregulation limits the synthesis of existing research findings and their dissemination to practitioners working in both performance and health contexts. Therefore, the purpose of the current review was threefold: first, we provide a broad overview of various autoregulation strategies and their development in both research and practice whilst highlighting the inconsistencies in definitions and terminology that currently exist. Second, we present an overarching conceptual framework that can be used to generate operational definitions and contextualise autoregulation within broader training theory. Finally, we show how previous definitions of autoregulation fit within the proposed framework and provide specific examples of how common practices may be viewed, highlighting their individual subtleties

Clusters, Concepts, and Pseudometrics

AbstractThe fields of cluster analysis and concept analysis are both used to identify patterns in data. Concept analysis identifies similarities between sets of objects based on their attributes. Cluster analysis groups objects with related characteristics based on some notion of distance.In this paper, we investigate connections between these two approaches. In particular, for each binary relation defined on a set of objects O and attributes, we define distance functions ρ (on the power set of) and δ (on O).We prove that ρ and δ are pseudometrics and use them to specify a clustering algorithm that computes a subset of the concept latticediscover new interpretations of basic notions in concept analysis.In particular, we characterize concepts in terms of ρ and characterize a family of concept lattices based on all subsets with a fixed cardinality bound in terms of δ.Our clustering algorithm differs from the classical algorithms since, first, the values of ρ, not δ, determine which pairs of sets are combined at each level, and second, the clusters defined at each level in the algorithm are generally anti-chains and may not be partitions. Therefore, the analysis of the algorithm depends on the metric-geometry of ρ and is more involved than the analysis of the classical algorithms.We have developed a software environment that permits the execution of the algorithm on finite relations and the storage and analysis of the resulting clusters. The algorithm has been run on relations generated from a variety of sources ranging from medical research to sporting events. Our results indicate that the number of iterations of the clustering algorithm is linear in the size of O and produces a linear number of clusters that are concepts. Hence the algorithm can be a useful tool for computing a tractable subset of a very large concept lattice

Readings in Civilizations

Second edition, revised. Readings selected by Professors Curran, Gradie, Roney and Siff for the History Department at Sacred Heart University. Table of contents: Greece -- Florence -- Industrial England -- China -- China narrative