The effectiveness of job specific training on the occupational performance of student nurses

Body mechanic checklist scores during a one-person pivot transfer, and boosting up in bed were evaluated to determine the effectiveness of training on the work performance of female student nurses from a local college. Thirty subjects participated in the study and were divided into a control group, an experimental group that received basic body mechanic training, and an experimental group that received job specific training. A one-way ANCOVA was calculated to examine the effects of the experimental procedures on the subjects' performance. This revealed a statistically significant difference between the groups (patient transfer F = 10.11, p value < 0.001; boosting F = 38.62, p value < 0.001). A post hoc analysis (Bonferroni procedure) indicated that the job specific training group (mean 11.65, SD 0.66) demonstrated a statistically significant improvement in their performance compared to the other two groups (control group mean 7.5, SD 0.67; BBMT mean 9.66, SD 0.67).     

Restoring complex vegetation in urban settings: The case of tidal freshwater marshes

Tidal freshwater marshes have diverse plant communities that vary spatially and temporally due to hydrology, animal activity, and other factors. Development of urban centers along rivers of the U.S. Atlantic coast has reduced the historic extent and quality of these and other coastal wetlands. Because the vegetation of these wetlands is more complex than that of salt and brackish marshes (where restoration of vegetation typical of natural systems has sometimes been successful), restoration of tidal freshwater marsh vegetation is likely to be more difficult, particularly in urban areas. Watershed urbanization alters hydrology, sediment load, propagule availability and composition, nutrient status, and other variables that together create an environment different from that of wetlands in less developed areas, possibly precluding restoration of typical marsh vegetation. Tidal freshwater wetlands were historically extensive along the Anacostia River in Washington, DC, but most of these were lost due to filling, dredging, or hydrologic alteration. Over the last decade, the U.S. Army Corps of Engineers has implemented projects designed to restore tidal freshwater wetlands along the Anacostia, which involved increasing elevation with dredged river sediment and planting native vegetation. To illustrate some of the mechanisms affecting vegetation development in restored tidal freshwater marshes in urban areas, I present a case study on one of these wetlands, Kingman Marsh, that also includes research at another restored wetland and two natural reference sites. Studies by my research groups indicate that the restored wetlands undergo essentially a planting-modified process of primary succession. Low densities of seeds are initially present in the substrate, and prolific seed dispersal into the restored sites results in high initial plant diversity comprised of plantings and ruderal (i.e. weedy) natives and exotics. Seed banks develop rapidly at the restored sites, probably due to colonization and early reproduction by ruderal species. Hydrology and disturbance by non-native animals (including resident Canada goose) are important variables controlling establishment of vegetation in these systems. Recent literature and the case study indicate that the environmental conditions of urban settings impose constraints in restored wetlands that result in plant communities more like those of urban natural wetlands than those of wetlands in less urbanized watersheds. This suggests that rather than design wetland restoration projects with the goal of creating pristine wetland vegetation, restorationists must identify, accept, and if possible capitalize on the ecological constraints of the urban environment in setting achievable and desirable restoration goals.     

Optimal estimation of a finite population mean under generalized random permutation models

Employing certain generalized random permutation models and a general class of linear estimators of a finite population mean, it is shown that many of the conventional estimators are “optimal” in the sense of minimum average mean square error. Simple proofs are provided by using a well-known theorem on UMV estimation. The results also cover certain simple response error situations.     

Government policies towards innovation: A review of empirical findings

Since the Second World War, governments in Western mixed economies have become increasingly involved in promoting technical innovation in industry. The analytical basis for this involvement is deficient, as is empirical information and analysis on its effects. But it is probable that, from an economic viewpoint, governments have been mistaken in supplementing normal industrial activity by financing large-scale development projects in technically sophisticated industry. They should instead be financing longer-term basic and applied research, as well as increasing technical awareness in more traditional industries. More needs to be known about the factors affecting innovative decisions in industrial firms, including the effects of industry-specific characteristics and of government policies.     

On rates of convergence to infinitely divisible laws for dependent random variables

Large O and small o approximations of the expected value of a class of functions (modified K-functional and Lipschitz class) of the normalized partial sums of dependent random variables by the expectation of the corresponding functions of infinitely divisible random variables have been established. As a special case, we have obtained rates of convergence to the Stable Limit Laws and to the Weak Laws of Large Numbers. The technique used is the conditional version of the operator method of Trotter and the Taylor expansion.     

A class of Shrunken estimators for normal mean

This paper presents a class of estimators for the mean of a normal population and determines the conditions on characterizing scalars under which the class of estimators uniformly dominates over the conventional sample mean according to the mean-square-error criterion.