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This 1984-85 statistical survey of libraries at four-year colleges and universities, two-year colleges, law libraries, and miscellaneous academic institutions in the Pacific Northwest provides relevant data for comparison and inventory purposes. A total of 98 institutions responded to the questionnaire, which was administered by the Pacific Northwest Library Association (PNLA). Although the current questionnaire follows past practice in order to provide comparable data, some changes have been implemented. Questions dealing with online interlibrary loan capability were omitted and several questions relating to usage were added; i.e., circulation figures, reference transactions, gate counts, bibliographic instruction statistics, database transactions, and hours of service. Divided by type of institution, data tables include but are not limited to the following topics: (1) rank by collection size; (2) volumes held as of June 1985; (3) volumes per full time student; (4) growth rate; (5) total microform units; (6) audiovisual units (broken into categories); (7) government documents; (8) number of items borrowed; (9) current serials; (10) total library operating expenses; (11) professional staff; (12) non-professional, non-student staff; (13) number of male/female professional staff; (14) number of hours in professional work week; (15) beginning professional salaries; and (16) director's salaries. The survey instrument, instructions for completing the questionnaire, and an index to respondents are included. (THC).

Objectives: To examine the sensitivity/specificity of the Athlete Psychological Strain Questionnaire (APSQ) in both male and female elite athletes, and also assess internal consistency and convergent/divergent validity, and determine discriminative validity relative to current injury status. Methods: Data were provided by 1093 elite athletes (males n=1007; females n=84). Scale validity and reliability values were benchmarked against validated measures of general psychological distress and well-being. ROC curve analysis determined a range of optimal severity cut-points. Results: Bias-corrected area under curve (AUC) values supported three APSQ cut-points for moderate (AUC=0.901), high (AUC=0.944) and very high (AUC=0.951) categories. APSQ total score Cronbach coefficients exceeded those observed for the Kessler 10 (K-10). Gender ×injury status interactions were observed for the APSQ total score and K-10, whereby injured female athletes reported higher scores relative to males and non-injured female counterparts. Conclusion: By providing a range of cut-off scores identifying those scoring in the marginal and elevated ranges, the APSQ may better facilitate earlier identification for male and female elite athletes vulnerable to mental health symptoms and developing syndromes. Use of the APSQ may support sports medicine practitioners and allied health professionals to detect early mental ill health manifestations and facilitate timely management and ideally, remediation of symptoms.

The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.