Inclusive Fitness and the Practice of Polyandry Among the Skidi Pawnee

The ethnohistorical record of the practice of polyandry among the Skidi Pawnee of the 19th century is examined from the perspective of the inclusive fitness model. The practice of temporary polyandry may have allowed males to maximize their inclusive fitness by insuring high paternity certainty. Younger brothers and nephews may have guarded the wives of older male relatives to prevent the wives from bearing children of unrelated males

Confidential Employees: A Recommendation for Uniformity

In NLRB v. Hendricks County Rural Electric Membership Corp., the Court held that there is a reasonable basis in law for the Board\u27s use of the \u27labor nexus test. At the same time, the Court declined to address the issue of whether the limited implied exclusion is also proper. This Note will address that open question by tracing the legislative, administrative and judicial treatment of confidential employees. The mode of analysis will be chronological, commencing with the passage of the Act. The analysis will detail the development of the labor nexus standard and the limited implied exclusion and will examine the different treatment afforded confidential employees by the Board and the courts in light of Hendricks. Finally, this Note will recommend that all confidential employees, determined to be so by a uniform standard, be treated uniformly

Early Findings From a Tri-county Collaborative Approach to Addressing the Opioid Crisis

While the opioid crisis has captured the concern of public health officials and the public, the epidemic is not evenly distributed. Rural communities are especially hard-hit, particularly areas with a large working-class population where dim economic prospects have led to dramatic increases in so-called “deaths of despair” (Case and Deaton, 2017). These communities bear a high share of opioid-related mortality, and also suffer from limited supports to treat addiction and related problems such as mental illness and chronic pain

BLAST: improvements for better sequence analysis

Basic local alignment search tool (BLAST) is a sequence similarity search program. The National Center for Biotechnology Information (NCBI) maintains a BLAST server with a home page at . We report here on recent enhancements to the results produced by the BLAST server at the NCBI. These include features to highlight mismatches between similar sequences, show where the query was masked for low-complexity sequence, and integrate information about the database sequences from the NCBI Entrez system into the BLAST display. Changes to how the database sequences are fetched have also improved the speed of the report generator

Soar-mode v5.0 User’s Manual for Soar release 5.2 and 6.0

Soar-mode is a major mode within the GNU-Emacs editor. It provides an integrated, structured editor for editing, running, and debugging Soar models on the production level. Productions are treated as first class objects. With keystroke (or menu) commands productions can be directly loaded, examined, and queried about their current match status. Listings of the productions that have fired or are about to fire can be automatically displayed. Soar-mode includes and organizes, for the first time, complete on-line documentation on Soar and a simple browser to examine this information

The Marian Forum Volume 3: Vessels of Clay

Proceedings of the 1963 Marian Forum edited by Alfred Isacsson, with papers by Thomas McGinnis, Gregory Smith, Eamon Carroll, Joachim Snyder, Anselm Burke, and Roland Murphy

Factors Influencing Post-adoptive Enterprise Resource Planning (ERP) Utilization

Organizations expend a great deal of time, effort and money on the implementation of enterprise resource planning (ERP) systems. They are considered the price of entry for large organizations to do business. Yet the success rate of ERP systems is poor. IS literature suggests that one possible reason for this is the underutilization of these systems. Existing ERP literature is replete with research to improve ERP project implementation success; however, notably absent from these streams is the research that identifies how ERP systems are utilized by individuals or organizations. This dissertation posits that increased ERP utilization can result from increased software and business process understanding gained from both formal training and experiential interventions. New dimensions of system utilization (required vs. optional) are proposed. The purpose of this dissertation is to examine how these interventions impact ERP utilization. The results of this dissertation show that while software-training interventions are important to understanding, it is the business process training interventions that seem to provide the greater effect on understanding. This increased understanding positively affects utilization scenarios where a mixture (required vs. optional) of software features and business process tasks can be leveraged by end-users. The improved understanding of post-adoptive ERP utilization gained from this study benefits both researchers and practitioners

A Mid-Holocene Fauna from Bear Den Cave, Sequoia National Park, California

Test excavation of floor fill deposits in the first room in Bear Den Cave, Sequoia National Park, produced fossiliferous sediments down to at least 40 cm depth. Radiocarbon analysis of charcoal from this layer indicates an earlymiddle Holocene age of 7220 CAL BP. The fossil accumulation represents prey recovered from generations of ringtail (Bassariscus astutus) dung. Microvertebrate remains include salamanders, lizards, snakes, and mammals. The recovery of Aneides ferreus/vagrans from early-middle Holocene deposits in Bear Den Cave is a first for this species group. Equally interesting is the recovery of Plethodon sp. Neither taxa live in the Sierra Nevada today. The fossil-rich deposits of Bear Den Cave indicate that future paleoecological studies will be productive in Sequoia National Park

Extracting biologically significant patterns from short time series gene expression data

<p>Abstract</p> <p>Background</p> <p>Time series gene expression data analysis is used widely to study the dynamics of various cell processes. Most of the time series data available today consist of few time points only, thus making the application of standard clustering techniques difficult.</p> <p>Results</p> <p>We developed two new algorithms that are capable of extracting biological patterns from short time point series gene expression data. The two algorithms, <it>ASTRO </it>and <it>MiMeSR</it>, are inspired by the <it>rank order preserving </it>framework and the <it>minimum mean squared residue </it>approach, respectively. However, <it>ASTRO </it>and <it>MiMeSR </it>differ from previous approaches in that they take advantage of the relatively few number of time points in order to reduce the problem from NP-hard to linear. Tested on well-defined short time expression data, we found that our approaches are robust to noise, as well as to random patterns, and that they can correctly detect the temporal expression profile of relevant functional categories. Evaluation of our methods was performed using Gene Ontology (GO) annotations and chromatin immunoprecipitation (ChIP-chip) data.</p> <p>Conclusion</p> <p>Our approaches generally outperform both standard clustering algorithms and algorithms designed specifically for clustering of short time series gene expression data. Both algorithms are available at <url>http://www.benoslab.pitt.edu/astro/</url>.</p

Inertial Sensors—Applications and Challenges in a Nutshell

This editorial provides a concise introduction to the methods and applications of inertial sensors. We briefly describe the main characteristics of inertial sensors and highlight the broad range of applications as well as the methodological challenges. Finally, for the reader’s guidance, we give a succinct overview of the papers included in this special issue