Trajectories of depression in different groups of retirees

The pattern of change in depression is based upon variables present at the time of retirement. Females have been found to have higher scores than males on some mental health outcomes but lower scores on others. Better health ratings have been found to be predictive of increased positive outcomes and decreased negative outcomes. Level of education has been found to be predictive of decreased negative mental health outcomes in retirement. Married individuals generally adjust better to retirement life than other individuals. Higher levels of income and greater job prestige are related to better outcomes in retirement and individuals. Results from a cluster analysis in this study identified three groupings of retirees. The first group consisted of both males and females working in managerial fields of work. The second group consisted largely of married men working in labor fields of work. The third group consisted of poor widows. These groups were found to be significantly different on a number of measures. A fairly strong linear component was found in depression scores over time for the sample as a whole, although this component did not quite achieve statistical significance (p = .067). The quadratic component was found to not be statistically significant (p = .464). The results changed after including the cluster membership in a growth curve model. The linear component was found to not be statistically significant for both the difference between the male laborer and manager groups (p = .462) and the poor widow and manager groups (p = .132). When a quadratic component was added to the growth curve model, the significance of the two linear components increased. Although the difference between the male laborer and manager groups did not reach statistical significance (p = .097), the difference between the poor widow and manager groups did become statistical significance (p = .013). For the non-linear component, the difference between the male laborer and manager groups did not reach statistical significance (p = .132) whereas the difference between the poor widow and manager groups did reach statistical significance (p = .034)

Evolution of Cooperative Thought, Theory, and Purpose

The evolution of agricultural cooperative thought, theory, and purpose in the United States is reviewed from the standpoint of the reemergence of interest in how cooperatives can provide some of the security and benefits that might be lost with gradual phasing out of federal government farm support programs. By accomplishing group action for self-help, the early development of cooperatives drew considerable attention from economists, social theorists, and politicians. Alternative schools of cooperative thought developed, but most proponents of cooperatives regarded them as having enormous potential to provide a public service role in building a more economically stable and democratic society This paper also surveys how cooperative theory was developed more rigorously in the post-WWII period. It has provided better analytical tools for understanding how and why cooperatives have changed in response to technological and economic developments, as well as to social trends, like individualism. Given the new perspectives on cooperative theory and the scope of changes in how cooperatives operate and are structured, cooperatives have even greater potential for coordinating self-help actions, but this potential needs the support of cooperative education services.Agribusiness,

Technology Transfer in Forest Pest Management: A Case History

The current approach being used in the spruce budworm technology transfer program for the Lake States is described. During 1981-1982, we concentrated on needs assessment surveys and the development and packaging of materials in five areas: general manual, chemical control handbook, silviculture handbook, instruction manual for remote sensing workshops, and technical reports on budworm impact on spruce-fir stands. We present a list of factors that researchers and technology transfer specialists should consider when plan- ning a research and technology transfer program in forest pest management

Closed loop fiber optic rotation sensor

An improved optical gyroscope is provided, of the type that passes two light components in opposite directions through an optic fiber coil, and which adds a small variable frequency to one of the light components to cancel the phase shift due to rotation of the coil. The amount of coil rotation from an initial orientation, is accurately determined by combining the two light components, one of which has a slightly increased frequency, to develop beats that each represent a predetermined angle of rotation. The direction of rotation is obtained by combining the two light components on a photodetector, intermittently phase shifting a single light component by 90 deg and comparing the direction of change of photodetector output (+ or -) caused by the 90 deg shift, with the slope (+ or -) of the photodetector output at about the same time, when there is a 90 deg shift

High-Throughput 3D Homology Detection via NMR Resonance Assignment

One goal of the structural genomics initiative is the identification of new protein folds. Sequence-based structural homology prediction methods are an important means for prioritizing unknown proteins for structure determination. However, an important challenge remains: two highly dissimilar sequences can have similar folds --- how can we detect this rapidly, in the context of structural genomics? High-throughput NMR experiments, coupled with novel algorithms for data analysis, can address this challenge. We report an automated procedure, called HD, for detecting 3D structural homologies from sparse, unassigned protein NMR data. Our method identifies 3D models in a protein structural database whose geometries best fit the unassigned experimental NMR data. HD does not use, and is thus not limited by sequence homology. The method can also be used to confirm or refute structural predictions made by other techniques such as protein threading or homology modelling. The algorithm runs in $O(pn^{5/2} \log {(cn)} + p \log p)$ time, where $p$ is the number of proteins in the database, $n$ is the number of residues in the target protein and $c$ is the maximum edge weight in an integer-weighted bipartite graph. Our experiments on real NMR data from 3 different proteins against a database of 4,500 representative folds demonstrate that the method identifies closely related protein folds, including sub-domains of larger proteins, with as little as 10-30\% sequence homology between the target protein (or sub-domain) and the computed model. In particular, we report no false-negatives or false-positives despite significant percentages of missing experimental data

An Improved Nuclear Vector Replacement Algorithm for Nuclear Magnetic Resonance Assignment

We report an improvement to the Nuclear Vector Replacement (NVR) algorithm for high-throughput Nuclear Magnetic Resonance (NMR) resonance assignment. The new algorithm improves upon our earlier result in terms of accuracy and computational complexity. In particular, the new NVR algorithm assigns backbone resonances without error (100% accuracy) on the same test suite examined in [Langmead and Donald J. Biomol. NMR 2004], and runs in $O(n^{5/2} \log {(cn)})$ time where $n$ is the number of amino acids in the primary sequence of the protein, and $c$ is the maximum edge weight in an integer-weighted bipartite graph

Developing skills with pre-service teachers

Teachers need to equip students with visual, written and verbal communication skills

3D-Structural Homology Detection via Unassigned Residual Dipolar Couplings

Recognition of a protein\u27s fold provides valuable information about its function. While many sequence-based homology prediction methods exist, an important challenge remains: two highly dissimilar sequences can have similar folds --- how can we detect this rapidly, in the context of structural genomics? High-throughput NMR experiments, coupled with novel algorithms for data analysis, can address this challenge. We report an automated procedure for detecting 3D-structural homologies from sparse, unassigned protein NMR data. Our method identifies the 3D-structural models in a protein structural database whose geometries best fit the unassigned experimental NMR data. It does not use sequence information and is thus not limited by sequence homology. The method can also be used to confirm or refute structural predictions made by other techniques such as protein threading or sequence homology. The algorithm runs in O(pnk3) time, where p is the number of proteins in the database, n is the number of residues in the target protein, and k is the resolution of a rotation search. The method requires only uniform 15N-labelling of the protein and processes unassigned 1H-15N residual dipolar couplings, which can be acquired in a couple of hours. Our experiments on NMR data from 5 different proteins demonstrate that the method identifies closely related protein folds, despite low-sequence homology between the target protein and the computed model