Purpose: With the growing importance of performance measurement and management, this exploratory study intends to examine the practices of maintenance managers with regards to maintenance measures, as used in their organizations. In this process, the study attempts to uncover the relevant maintenance performance dimensions from the perspectives of the surveyed managers. In addition, the mediating effect of information availability on the main performance measures utilization is studied. Design/methodology/approach: The research at hand is survey-based. It utilizes the responses of a sample of ninety-five (95) experienced maintenance managers to identify the most relevant maintenance performance measures. Factor analysis is then utilized to uncover the important dimensions of performance, as seen by the respondents. Additionally, using the Partial Least Squares method, several models were studied. Findings: The findings of this exploratory research appear to suggest that maintenance managers are beginning to broaden their perspective with regard to performance management. While machine and plant-related performance measures are still emphasized, maintenance managers are slowly moving toward a wider organizational orientation. While the manufacturing organizations are becoming more and more customer-oriented open systems, the maintenance function of these organizations is still, for the most part, operating under the semi-open system orientation. Overall, it appears that an emerging maintenance strategy is slowly taking shape. Research limitations/implications: For the most part, performance measures and measurement related to maintenance have not received enough attention from researchers. Therefore, the literature dealing with the different facets of performance in maintenance has not been forthcoming. The study attempts to fill this apparent gap in the literature. This is important, as maintenance managers are being asked to contribute to the achievement of the competitive strategies of their organizations. Therefore, they must quickly learn how to view maintenance from a coherent strategic organizational perspective. Such a perspective should help in integrating the maintenance, resources, capabilities, and technical know-how in order to serve the strategic goal of their organization. The research at hand is limited to a sample from Portugal. Therefore, the results and conclusions must be interpreted accordingly. Practical implications: As maintenance managers struggle to move from a machine-orientation to a more organizational-wide strategic orientation, they are often left with many questions and few answers. This study attempts to bring this problem to the spotlight so that it can receive more systematic empirical and practical research. In this context, the role of maintenance managers in the process of organizational strategy formulation should be examined. Originality/value: The study presented in this article has practical, as well as theoretical contributions. It deals with an area of performance measurement, which so far has been relatively ignored. It uses a system orientation (closed vs open), in addition to the strategic orientation (single vs multi-faceted strategy) in order to shed some light on the need to have consistency between the nature of the system and its strategic objective.

In this reviewwe discuss methodology to ascertain the amount of information in given data sets with respect to determination of model parameters with desired levels of uncertainty.We do this in the context of least squares (ordinary,weighted, iterative reweightedweighted or "generalized", etc.) based inverse problem formulations. The ideas are illustrated with several examples of interest in the biological and environmental sciences.

In this note we explain the use of the Akiake Information Criterion and its related model comparison indices (usually derived for maximum likelihood estimator inverse problem formulations) in the context of least squares (ordinary, weighted, iterative weighted or “generalized”, etc.) based inverse problem formulations. The ideas are illustrated with several examples of interest in biology.

Background – This study is an attempt to explore the relationship between microcredit and the socio-economic empowerment of women in rural Bangladesh. Microcredit is simply the extension of a small amount of collateral-free institutional loans to jointly liable poor group members to generate employment and income enhancing activities. As it is too difficult for poor members to get loan from the formal credit institutions, Grameen Bank (GB) or other Non-Government Organizations (NGOs) provide small loans to vulnerable groups of the society by which they are expected to empower over his counterparts. Research questions – RQ1: How does micro-credit affect different indicators of women empowerment in the rural areas of Bangladesh? RQ2– Is the impact different from the male counterparts in the sample households? Purpose – This study is an effort to find the impact of microcredit on a number of indicators of women’s empowerment in the rural areas in Bangladesh. Methodology – Quantitative Regression Techniques such as Ordinary Least Square (OLS) and Instrumental Variable (IV) method have been applied to get the relationship between microcredit and women empowerment. Conclusion – Applying nationally representative cross-section survey data, Bangladesh Integrated Household Survey (BIHS) 2015, this thesis is intended to find the causal linkage between microcredit and women empowerment’s with different dimensions of women’s decisions are taken as empowerment indicators: production, resources, income, leadership, savings and time. The analysis has been conducted at the household level. The study assumes that women empowerment is endogenous. After controlling for endogeneity in the estimation by using an instrumental variable (IV) ‘distance to the market’ this study finds a significant relationship between microcredit and different dimensions of women’s empowerment. Participation in the microcredit program is found to be significant in explaining some of the outcome indicators of empowerment for the sampled households.

The reproductive biology of the least chub Iotichthys phlegethontis (Cope) was studied from June 1976 to March 1978. Fish from both field and laboratory populations of the Leland Harris Spring Complex, Juab Co., Utah were utilized in the study. Reproduction in 1977 occurred from April to July in the field population and from April through August in the laboratory population. Reproduction was determined from gross examination and weight measurements of testes and ovaries, breeding coloration in males and diameter measurements of ova. Males and females matured at about the same size, 28 to 30 mm TL. The number of mature ova produced during spawning ranged from 283 to 2752 for females 31 to 46 mm TL. Mature ova ranged in size from 0.8 to 1.28 mm. Least chub are partial and intermittent spawners. This conclusion is supported by ova diameter measurements and calculations of the duration and peak period of spawning. Least chub are polyandrous broadcast spawners over vegetation. The eggs are demersal and adhesive. The egg incubation period was 2.1 days at 22.2 C. The eleutheroembryo are approximately 4 mm in length. They are not photophobic and appear to have cement glands. Specific characteristics of reproduction are discussed in relation to ecological conditions of the habitat.

Thesis. 1977. M.S.--Massachusetts Institute of Technology. Dept. of Meteorology. / Microfiche copy available in Archives and Science. / Bibliography : leaves 49-51. / M.S.

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White-tailed deer (Odocoileus virginianus) dispersal and excursion movements impact gene flow, population dynamics, and disease spread. Knowledge of movement characteristics and habitat selection during dispersal could provide the ability to predict how deer may relocate themselves within the landscape while providing managers valuable information regarding corridors for gene flow and disease spread. My objectives were to 1) test the hypothesis that extra-home-range movements occur as a strategy to broaden mating opportunities or as a means of searching for higher quality resources in this fragmented landscape, 2) compare occurrence rates and path movement metrics for dispersal and excursion movements to determine if underlying differences in behavior exist that would allude to mechanisms for accepting the risk of leaving a home range, 3) create and test the performance of expert opinion and step selection function resistance models at predicting deer dispersal movements, and 4) fit single and multiple random walk models to dispersal path data to determine movement states occurring within this behavior. During 2011-2014, I placed GPS collars programmed to take hourly locations on 49 fawn and yearling white-tailed deer in agricultural east-central Illinois to record dispersal and excursion movement paths. Linear mixed effects models were used to test for differences in path characteristics between sexes and ages (e.g., distance, straightness, duration, and speed). I used known-fate models, with demographic, temporal, and home range variables as covariates, to obtain dispersal and excursion occurrence rate estimates. Ten dispersal and 54 excursion movement paths were recorded during the study. Dispersal paths were longer and straighter (P < 0.001), and trended toward being longer in duration (P = 0.080) and faster in speed (P = 0.085), than excursion paths. Dispersal rates differed by sex (annual estimate ± SE with ages pooled: males 0.81 ± 0.12, females 0.16 ± 0.15) and were greatest during the breeding season (14-day estimates for males: winter 0.00 ± 0.01, fawning 0.02 ± 0.1, prebreeding 0.01 ± 0.01, and breeding 0.31 ± 0.15, and females: winter 0.00 ± 0.01, fawning 0.01 ± 0.1, prebreeding 0.01 ± 0.01, and breeding 0.04 ± 0.03). In contrast, I found no evidence that excursion rates were influenced by demographic, temporal, or home range variables (annual: 0.78 ± 0.06). I compared 2 methods of resistance modeling for predicting deer dispersal paths. I created an expert opinion survey and calculated a dispersal step selection function (SSF) to rank habitat variables and create 2 types of resistance maps to dispersal movements. I created least-cost paths with the starting and ending points coinciding with recorded dispersal paths within these 2 resistance maps. I compared the created paths to actual paths and a null straight line path using a path deviation index (PDI), path straightness, and path cost/m as variables of interest. Experts ranked land cover variables differently by season, applying a lower resistance value to agriculture cover during the summer/fall period, so 2 versions of the expert opinion resistance maps were created. For the SSF, I found that both forest cover and streams had significant nonlinear effects on deer dispersal movements. Assuming that all other factors remained constant, deer were more likely (≥ 0.50 probability) to move toward forested habitat when located < 335 m and when > 2795 m away. Deer dispersal movement behavior relating to streams followed a similar trend but with deer always having > 0.56 probability to move toward a stream than away. For least-cost path comparison, I conducted 3 ANOVAs (α = 0.05 throughout) to test for mean differences in calculated path metrics for all paths with path type as a within-subjects effect. I found no difference between the expert opinion survey model, the SSF model, and the null straight line model at predicting dispersal paths. PDI values were similar among all models (F1,9 = 0.004, P = 0.99). The SSF paths (0.91 ± 0.02) were significantly straighter then both the expert opinion (0.57 ± 0.03) and actual deer paths (0.44 ± 0.06; F1, 9 = 32.65, P < 0.001), but the expert opinion path did not differ from the actual path (P = 0.08). Path costs differed within the expert opinion survey resistance map (F1, 9 = 14.21, P < 0.001) with the expert opinion least cost paths (23.64 ± 3.14) having lower resistance/m than both the actual (46.15 ± 3.85) and straight line paths (48.74 ± 3.94; P < 0.001 for both). However, the actual and straight line paths did not differ (P = 0.872). There were no difference in path costs between the actual, SSF least-cost path, and straight line paths within the SSF resistance map (F1, 9 = 0.454, P = 0.64). I constructed and attempted to fit single and multiple random models to collected dispersal locations using WinBUGS v. 1.4.3. I was able to fit a single random walk model to deer dispersal paths but the more complex random walk models did not converge. I used the average parameter values derived from the single model to simulate deer dispersal paths and compared them to observed Net Squared Displacement. My simulated paths underpredicted deer displacement for 0.90 of individuals. Deer in east-central Illinois are very mobile and commonly make excursion movements throughout the year. The fact that I recorded differing dispersal rates within the same study area over a temporally short period from a previous study highlight the need for managers to obtain recent estimates of population parameters when making management decisions. The frequency of excursion movements should not be overlooked by managers as it is a behavior that can influence gene flow and potentially spread disease across the landscape at a localized scale. The preference for forest and stream habitats during dispersal can allow managers to focus surveillance or culling efforts around these types of habitats. The application of the least-cost path modeling technique appears to be ineffective at predicting deer dispersal paths, which emphasizes the importance of validating these types of models with actual data. The results from the random walk analysis highlight the need to collect as many locations as possible during temporally-short movements to understand the mechanisms acting upon them.