Structural change and productivity growth, 20 years later: old problems, new opportunities

Includes bibliography

Structural change and productivity growth 20 years later: old problems, new opportunities. Summary

Includes bibliography

The new metal worker pattern book; a complete course of instruction in the modern methods of developing and cutting the patterns for sheet metal work, giving the principles underlying practically every problem that is likely to come up in practice and explaining the selection and use of drawing tools and linear and geometrical drawing so clearly that one, who has had no previous knowledge of arithmetic or drawing, may understand these essentials and apply them in using the 253 problems in the development of patterns by the parallel line, conical or flaring, and triangulation systems.

Mode of access: Internet.

Brickwork, a practical treatise embodying the general and higher principles of bricklaying, cutting and setting ... and a series of problems in applied geometry,

Mode of access: Internet.

Operator's manual : fixture, lathe, metal cutting for 2 inch diameter round or 2 inch square stock, 360 degree index ring, 12-1/2 high, 5 wide, 3-7/8 vertical travel (Numeric Products Company model 312) (3465-022-8817).

"29 November 1967."

Recommendations of the Bureau of Animal Industry on problems of livestock production : prepared for the information of livestock owners, agricultural writers, county agents, livestock specialists, the meat trade, bureau employees and others interested in the betterment of the live stock industry /

Contribution from Bureau of Animal Industry.

Stereotomy. Problems in stone cutting. In four classes.

Mode of access: Internet.

Comparison of three algorithms for nonlinear metal cutting problems

This paper compares three alternative numerical algorithms applied to a nonlinear metal cutting problem. One algorithm is based on an explicit method and the other two are implicit. Domain decomposition (DD) is used to break the original domain into subdomains, each containing a properly connected, well-formulated and continuous subproblem. The serial version of the explicit algorithm is implemented in FORTRAN and its parallel version uses MPI (Message Passing Interface) calls. One implicit algorithm is implemented by coupling the state-of-the-art PETSc (Portable, Extensible Toolkit for Scientific Computation) software with in-house software in order to solve the subproblems. The second implicit algorithm is implemented completely within PETSc. PETSc uses MPI as the underlying communication library. Finally, a 2D example is used to test the algorithms and various comparisons are made.

Correct procedures and cutting corners: a qualitative study of women's occupational health and safety in a beauty therapy industry

Objective: To examine the context of occupational health and safety related to blood-borne communicable diseases practice. Methods: A case study approach using qualitative semi-structured interviews with five key informants who represented different sectors of the beauty therapy industry in South Australia. Results: Four main themes were identified: (i) exposure to blood and blood-borne communicable diseases; (ii) prevention in practice; (iii) OH&S problems; and (iv) industry needs. Conclusion: Key OH&S issues in the beauty therapy industry include: power relationships between employers and employees, equipment costs, the need for more continuing education, and monitoring of practitioners. Implications: Economic constraints, continuing education, and government regulation of the beauty therapy industry are highlighted as significant areas for further consideration in addressing the OH&S needs of practitioners and their clients.

Production of cuttings in response to stock plant temperature in the subtropical eucalypts, Corymbia citriodora and Eucalyptus dunnii

Propagation of subtropical eucalypts is often limited by low production of rooted cuttings in winter. This study tested whether changing the temperature of Corymbia citriodora and Eucalyptus dunnii stock plants from 28/23A degrees C (day/night) to 18/13A degrees C, 23/18A degrees C or 33/28A degrees C affected the production of cuttings by stock plants, the concentrations of Ca and other nutrients in cuttings, and the subsequent percentages of cuttings that formed roots. Optimal temperatures for shoot production were 33/28A degrees C and 28/23A degrees C, with lower temperatures reducing the number of harvested cuttings. Stock plant temperature regulated production of rooted cuttings, firstly by controlling shoot production and, secondly, by affecting the ensuing rooting percentage. Shoot production was the primary factor regulating rooted cutting production by C. citriodora, but both shoot production and root production were key determinants of rooted cutting production in E. dunnii. Effects of lower stock plant temperatures on rooting were not the result of reduced Ca concentration, but consistent relationships were found between adventitious root formation and B concentration. Average rooting percentages were low (1-15% for C. citriodora and 2-22% for E. dunnii) but rooted cutting production per stock plant (e.g. 25 for C. citriodora and 52 for E. dunnii over 14 weeks at 33/28A degrees C) was sufficient to establish clonal field tests for plantation forestry.

Bayesian fisheries stock assessment: integrating and updating knowledge

In this thesis the use of the Bayesian approach to statistical inference in fisheries stock assessment is studied. The work was conducted in collaboration of the Finnish Game and Fisheries Research Institute by using the problem of monitoring and prediction of the juvenile salmon population in the River Tornionjoki as an example application. The River Tornionjoki is the largest salmon river flowing into the Baltic Sea. This thesis tackles the issues of model formulation and model checking as well as computational problems related to Bayesian modelling in the context of fisheries stock assessment. Each article of the thesis provides a novel method either for extracting information from data obtained via a particular type of sampling system or for integrating the information about the fish stock from multiple sources in terms of a population dynamics model. Mark-recapture and removal sampling schemes and a random catch sampling method are covered for the estimation of the population size. In addition, a method for estimating the stock composition of a salmon catch based on DNA samples is also presented. For most of the articles, Markov chain Monte Carlo (MCMC) simulation has been used as a tool to approximate the posterior distribution. Problems arising from the sampling method are also briefly discussed and potential solutions for these problems are proposed. Special emphasis in the discussion is given to the philosophical foundation of the Bayesian approach in the context of fisheries stock assessment. It is argued that the role of subjective prior knowledge needed in practically all parts of a Bayesian model should be recognized and consequently fully utilised in the process of model formulation.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

Essays on Stock Options, Incentives, and Managerial Action

Executive compensation and managerial behavior have received an increasing amount of attention in the financial economics literature since the mid 1970s. The purpose of this thesis is to extend our understanding of managerial compensation, especially how stock option compensation is linked to the actions undertaken by the management. Furthermore, managerial compensation is continuously and heatedly debated in the media and an emerging consensus from this discussion seems to be that there still exists gaps in our knowledge of optimal contracting. In Finland, the first executive stock options were introduced in the 1980s and throughout the last 15 years it has become increasingly popular for Finnish listed firms to use this type of managerial compensation. The empirical work in the thesis is conducted using data from Finland, in contrast to most previous studies that predominantly use U.S. data. Using Finnish data provides insight of how market conditions affect compensation and managerial action and provides an opportunity to explore what parts of the U.S. evidence can be generalized to other markets. The thesis consists of four essays. The first essay investigates the exercise policy of the executive stock option holders in Finland. In summary, Essay 1 contributes to our understanding of the exercise policies by examining both the determinants of the exercise decision and the markets reaction to the actual exercises. The second essay analyzes the factors driving stock option grants using data for Finnish publicly listed firms. Several agency theory based variables are found to have have explanatory power on the likelihood of a stock option grant. Essay 2 also contributes to our understanding of behavioral factors, such as prior stock return, as determinants of stock option compensation. The third essay investigates the tax and stock option motives for share repurchases and dividend distributions. We document strong support for the tax motive for share repurchases. Furthermore, we also analyze the dividend distribution decision in companies with stock options and find a significant difference between companies with and without dividend protected options. We thus document that the cutting of dividends found in previous U.S. studies can be avoided by dividend protection. In the fourth essay we approach the puzzle of negative skewness in stock returns from an altogether different angle than in previous studies. We suggest that negative skewness in stock returns is generated by management disclosure practices and find proof for this. More specifically, we find that negative skewness in daily returns is induced by returns for days when non-scheduled firm specific news is disclosed.

Estimation of cutting volume with three inventory methods for harvest planning in Canadian boreal forests.

Two methods of pre-harvest inventory were designed and tested on three cutting sites containing a total of 197 500 m3 of wood. These sites were located on flat-ground boreal forests located in northwestern Quebec. Both methods studied involved scaling of trees harvested to clear the road path one year (or more) prior to harvest of adjacent cut-blocks. The first method (ROAD) considers the total road right-of-way volume divided by the total road area cleared. The resulting volume per hectare is then multiplied by the total cut-block area scheduled for harvest during the following year to obtain the total estimated cutting volume. The second method (STRATIFIED) also involves scaling of trees cleared from the road. However, in STRATIFIED, log scaling data are stratified by forest stand location. A volume per hectare is calculated for each stretch of road that crosses a single forest stand. This volume per hectare is then multiplied by the remaining area of the same forest stand scheduled for harvest one year later. The sum of all resulting estimated volumes per stand gives the total estimated cutting-volume for all cut-blocks adjacent to the studied road. A third method (MNR) was also used to estimate cut-volumes of the sites studied. This method represents the actual existing technique for estimating cutting volume in the province of Quebec. It involves summing the cut volume for all forest stands. The cut volume is estimated by multiplying the area of each stand by its estimated volume per hectare obtained from standard stock tables provided by the governement. The resulting total estimated volume per cut-block for all three methods was then compared with the actual measured cut-block volume (MEASURED). This analysis revealed a significant difference between MEASURED and MNR methods with the MNR volume estimate being 30 % higher than MEASURED. However, no significant difference from MEASURED was observed for volume estimates for the ROAD and STRATIFIED methods which respectively had estimated cutting volumes 19 % and 5 % lower than MEASURED. Thus the ROAD and STRATIFIED methods are good ways to estimate cut-block volumes after road right-of-way harvest for conditions similar to those examined in this study.

Economic Effects of Global Warming under Stock Growth Uncertainty: The European Sardine Fishery

Global warming of the oceans is expected to alter the environmental conditions that determine the growth of a fishery resource. Most climate change studies are based on models and scenarios that focus on economic growth, or they concentrate on simulating the potential losses or cost to fisheries due to climate change. However, analysis that addresses model optimization problems to better understand of the complex dynamics of climate change and marine ecosystems is still lacking. In this paper a simple algorithm to compute transitional dynamics in order to quantify the effect of climate change on the European sardine fishery is presented. The model results indicate that global warming will not necessarily lead to a monotonic decrease in the expected biomass levels. Our results show that if the resource is exploited optimally then in the short run, increases in the surface temperature of the fishery ground are compatible with higher expected biomass and economic profit.