Condition indices are widely used to generate biological insight. However, purported relationships to indices are imprecise or inconsistent in the wild. I investigated factors influencing relative weight (Wr), a condition index commonly applied to fish. I first examined the relationship of Wr to physiology in two bluegill Lepomis macrochirus populations over a year. I regressed tissue composition (percentages of lipid, protein and water) and organ indices (liver-, gonad-, and viscerosomatic indices) on Wr. The regression model had little explanatory power (adjusted R2 = 0.14). Lipid was most influential (partial R2 = 0.11), but correlation strength fluctuated by season and population. To test the generality of these results, I performed a similar regression on a bluegill population with higher average Wr. Again, variables were not well correlated to Wr (adjusted R2 = 0.13). Combining comparable data sets increased Wr range 64% but explanatory power was low (adjusted R2 = 0.41) Both studies showed that expected correlations of physiological variables to Wr can be confounded in natural environments. To examine differences between natural and laboratory environments, I manipulated initial Wr and ration of juvenile bluegills. Although organ indices and tissue composition of all groups changed in time ((Wilks' Δ > 0.387, P > 0.03), no temporal pattern matched to Wr. At termination, all variables showed high correlations to Wr (r2 > 0.64). Correlation strength increased with time in the laboratory. Both ration and environment influenced correlations. Lastly, I examined differences in interpretation of Wr for chain pickerels Esox niger, largemouth bass Micropterus salmoides, and black crappies Pomoxis nigromaculatus. Regression models were compared to concurrent bluegill models. Piscivore models fit well (adjusted R2 > 0.50), whereas bluegill models had the lowest explanatory power (adjusted R2 = 0.13 and 0.14). Ecological specialization affected correlations to Wr. Theoretically, condition index values are determined by resource acquisition versus expenditure. Exact physiological expression is determined by life history and performance. Condition indices are imprecise predictors but track net somatic investment with great generality. Ancillary data, such as growth or length-at-maturity, may clarify interpretation. Condition indices should be used as qualitative monitoring tools, not omnibus physiological predictors. / Ph. D.

In most Puerto Rico reservoirs, Largemouth Bass Micropterus salmoides are typically fast-growing with distributions composed of distinct year-classes. Cerrillos Reservoir, however, displays the classic characteristics of a crowded bass population common in temperate lakes and ponds with fish stockpiling into a single modal distribution of slow-growing fish. This developed shortly after stocking in 1997, with the population quickly expanding to carrying capacity. Consequently, relative weight declined from above 100 to about 80 and the population was mostly composed of fish <=350 mm. A protected slot limit (356-508 mm) was implemented; however, limited effort and angler attitudes towards harvest of small bass prevented the success of this regulation, which was subsequently removed. In this dissertation, I examined the efficacy of using targeted management harvests for improving growth, size structure, and condition of Largemouth Bass in Cerrillos Reservoir. I used bioenergetics modeling to simulate the effects of targeted harvests. I predicted annual consumption of stock and quality-sized Largemouth Bass and used these estimates to model the effects of population reduction on consumption and growth of remaining bass. To validate the model, experimental removals of Largemouth Bass from the crowded size classes (200-380 mm) were conducted in 2012 and 2013. In these two years, I removed 20% and 22% of the total biomass, respectively. Following the experimental removals, mean condition of Largemouth Bass increased from 83 to 90, and increases were observed in all Largemouth Bass size categories. The reduction in predator abundance resulted in increased prey availability and smaller size structure of sunfish (Lepomis spp.) and tilapia (Coptodon and Oreochromis spp.) populations. I concluded that reducing Largemouth Bass abundance in Cerrillos Reservoir can move population dynamics toward desired management outcomes, but these actions must continue indefinitely to achieve success and sustainability. Annual management harvests are feasible but impractical, so I recommend increasing angler harvest and implementing management efforts designed to limit recruitment (e.g., shoreline rotenone application) to achieve management goals.

The purpose of this research was to evaluate current management strategies for the New River, Virginia, muskellunge Esox masquinongy fishery, which is the premier muskellunge fishery in the state. The primary objectives were to evaluate potential benefits and angler support for more restrictive harvest regulations and to quantify habitat selection at multiple spatial scales. A secondary objective was to develop an alternative procedure for testing differences in muskellunge condition from relative weight Wr data that incorporates uncertainty regarding the accuracy of the standard weight equation and that is based on derived statistical properties of the Wr index. Abundance of memorable-length (³1,070 mm) muskellunge was predicted to increase with minimum length limits of 914, 1,016, and 1,143 mm. Although yield per recruit would decline under a 1,143-mm minimum length limit, it was predicted to remain fairly stable at length limits of 914 and 1,016 mm due to fast growth rates of young fish. Even though most anglers defined trophy muskellunge to be in excess of 1,016 mm, angler support for length limits in excess of 1,000 mm was low. Habitat variables that were most strongly related to muskellunge habitat selection were measures of patch shape complexity and water depth. Increased river discharge was found to significantly affect muskellunge habitat use and selection, with fish abandoning deeper open-water habitats and moving to shallower areas closer to the shoreline during periods of high discharge. As for the secondary objective, a new statistical test (R-test) was developed that can be used to test for differences in Wr between and within fish stocks. Comparison with other statistical tests indicated that the R test provides more conservative results than traditional statistic procedures, and that substantial variability in standard weight equations will make it more difficult to detect statistical differences. Management recommendations for the New River muskellunge fishery include increasing the minimum length limit to approximately 965 to 1,067 mm and limiting the stocking of muskellunge only to those areas with sufficient juxtaposition of shallow- and deep-water habitat patches. / Ph. D.

試題難易度評量一直是許多人研究的課題。但傳統方法的五點量表問卷只提供固定尺度的選擇，似乎無法完整地表達受測者真實且複雜的思考。因此本文將以模糊問卷調查進行試題難易度的探討。許多研究應用模糊平均數、模糊眾數或模糊中位數等概念於試題難易度評量。而本文將以此為基礎，定義一種新的距離，再透過一些轉換取得試題的難易度指標，進而比較各試題之間難度的差異。本文的另一個重點，是各個不同難度因子的向度來決定各試題的難度。再以模糊相對權重的概念，對各向度的難易度指標作加權，進而比較、分析。 / Assessment for test difficulty have been the subject of many studies. The traditional method of a Likert scale questionnaire provides only a fixed scale choice, but it seems that we can’t fully express the real and complex thinking of respondents. Therefore, the thesis will apply fuzzy questionnaire to probe into test difficulty. Concepts such as Fuzzy mean, Fuzzy mode or Fuzzy median are applied in studies of assessment for test difficulty. The thesis will be based on these conceptions to define a new distance, and obtain the difficulty index of test through some conversion. Moreover, it will compare the differences of difficulty among test items. Another focus of this paper is to determine the difficulty of each item according to various dimensions of difficulty factors. Afterwards, the difficulty index of each dimension will be weighted, compared, and analyzed with the concept of fuzzy relative weight.

<p dir="ltr">Automaticity, an essential attribute of skill, is developed when a task is executed repeatedly with minimal attention and can have both good (e.g., productivity, skill acquisitions) and bad (e.g., accident involvement) implications on workers’ performance. However, the implications of automaticity in construction are unknown despite their significance. To address this knowledge gap, this research aimed to examine methods that are indicative of the development of automaticity on construction sites and its implications on construction safety and productivity. The objectives of the dissertation include: 1) examining the development of automaticity during the repetitive execution of a primary task of roofing construction and a concurrent secondary task (a computer-generated audio-spatial processing task) to measure attentional resources; 2) using eye-tracking metrics to distinguish between automatic and nonautomatic subjects and determine the significant factors contributing to the odds of automatic behavior; 3) determining which personal characteristics (such as personality traits and mindfulness dimensions) better explain the variability in the attention of workers while developing automaticity. To achieve this objective, 28 subjects were recruited to take part in a longitudinal study involving a total of 22 repetitive sessions of a simulated roofing task. The task involves the installation of 17 pieces of 25 ft2 shingles on a low-sloped roof model that was 8 ft wide, 8 ft long, and 4 ft high for one month in a laboratory. The collected data was analyzed using multiple statistical and data mining techniques such as repeated measures analysis of variance (RM-ANOVA), pairwise comparisons, principal component analysis (PCA), support vector machine (SVM), binary logistic regression (BLR), relative weight analyses (RWA), and advanced bootstrapping techniques to address the research questions. First, the findings showed that as the experiment progressed, there were significant improvements in the mean automatic performance measures such as the mean primary task duration, mean primary task accuracy, and mean secondary task score over the repeated measurements (p-value < 0.05). These findings were used to demonstrate that automaticity develops during repetitive construction activities. This is because these automatic performance measures provide an index for assessing feature-based changes that are synonymous with automaticity development. Second, this study successfully used supervised machine learning methods including SVM to classify subjects (with an accuracy of 76.8%) based on their eye-tracking data into automatic and nonautomatic states. Also, BLR was used to estimate the probability of exhibiting automaticity based on eye-tracking metrics and ascertain the variables significantly contributing to it. Eye-tracking variables collected towards safety harness and anchor, hammer, and work area AOIs were found to be significant predictors (p < 0.05) of the probability of exhibiting automatic behavior. Third, the results revealed that higher levels of agreeableness significantly impact increased levels of change in attention to productivity-related cues during automatic behavior. Additionally, higher levels of nonreactivity to inner experience significantly reduce the changes in attention to safety-related AOIs while developing automaticity. The findings of this study provide metrics to assess training effectiveness. The findings of this study can be used by practitioners to better understand the positive and negative consequences of developing automaticity, measure workers’ performance more accurately, assess training effectiveness, and personalize learning for workers. In long term, the findings of this study will also aid in improving human-AI teaming since the AI will be better able to understand the cognitive state of its human counterpart and can more precisely adapt to him or her.</p>