University of Alberta

About: University of Alberta is a education organization based out in Edmonton, Alberta, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 65403 authors who have published 154847 publications receiving 5358338 citations. The organization is also known as: Ualberta & UAlberta.

Why Do Some Family Businesses Out‐Compete? Governance, Long‐Term Orientations, and Sustainable Capability

Abstract: This article seeks to link the domains of corporate governance, investment policies, competitive asymmetries, and sustainable capabilities. Conditions such as concentrated ownership, lengthy tenure...

Discovering word senses from text

Abstract: Inventories of manually compiled dictionaries usually serve as a source for word senses. However, they often include many rare senses while missing corpus/domain-specific senses. We present a clustering algorithm called CBC (Clustering By Committee) that automatically discovers word senses from text. It initially discovers a set of tight clusters called committees that are well scattered in the similarity space. The centroid of the members of a committee is used as the feature vector of the cluster. We proceed by assigning words to their most similar clusters. After assigning an element to a cluster, we remove their overlapping features from the element. This allows CBC to discover the less frequent senses of a word and to avoid discovering duplicate senses. Each cluster that a word belongs to represents one of its senses. We also present an evaluation methodology for automatically measuring the precision and recall of discovered senses.

Sequence stratigraphy: methodology and nomenclature

Abstract: The recurrence of the same types of sequence stratigraphic surface through geologic time defines cycles of change in accommodation or sediment supply, which correspond to sequences in the rock record. These cycles may be symmetrical or asymmetrical, and may or may not include all types of systems tracts that may be expected within a fully developed sequence. Depending on the scale of observation, sequences and their bounding surfaces may be ascribed to different hierarchical orders. Stratal stacking patterns combine to define trends in geometric character that include upstepping, forestepping, backstepping and downstepping, expressing three types of shoreline shift: forced regression (forestepping and downstepping at the shoreline), normal regression (forestepping and upstepping at the shoreline) and transgression (backstepping at the shoreline). Stacking patterns that are independent of shoreline trajectories may also be defined on the basis of changes in depositional style that can be correlated regionally. All stratal stacking patterns reflect the interplay of the same two fundamental variables, namely accommodation (the space available for potential sediment accumulation) and sediment supply. Deposits defined by specific stratal stacking patterns form the basic constituents of any sequence stratigraphic unit, from sequence to systems tract and parasequence. Changes in stratal stacking patterns define the position and timing of key sequence stratigraphic surfaces. Precisely which surfaces are selected as sequence boundaries varies as a function of which surfaces are best expressed within the context of the depositional setting and the preservation of facies relationships and stratal stacking patterns in that succession. The high degree of variability in the expression of sequence stratigraphic units and bounding surfaces in the rock record means ideally that the methodology used to analyze their depositional setting should be flexible from one sequence stratigraphic approach to another. Construction of this framework ensures the success of the method in terms of its objectives to provide a process-based understanding of the stratigraphic architecture. The purpose of this paper is to emphasize a standard but flexible methodology that remains objective.

Cells of the adult human heart.

Abstract: Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require a deeper understanding of the molecular processes involved in the healthy heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavour. Here, using state-of-the-art analyses of large-scale single-cell and single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, and reveal distinct atrial and ventricular subsets of cells with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment, we identify cardiac-resident macrophages with inflammatory and protective transcriptional signatures. Furthermore, analyses of cell-to-cell interactions highlight different networks of macrophages, fibroblasts and cardiomyocytes between atria and ventricles that are distinct from those of skeletal muscle. Our human cardiac cell atlas improves our understanding of the human heart and provides a valuable reference for future studies.