Ex ante evaluations of alternate data structures for end user queries: Theory and experimental test

The data structure of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. This research develops a methodology for evaluating, ex ante, the relative desirability of alternative data structures for end user queries. This research theorizes that the data structure that yields the lowest weighted average complexity for a representative sample of information requests is the most desirable data structure for end user queries. The theory was tested in an experiment that compared queries from two different relational database schemas. As theorized, end users querying the data structure associated with the less complex queries performed better Complexity was measured using three different Halstead metrics. Each of the three metrics provided excellent predictions of end user performance. This research supplies strong evidence that organizations can use complexity metrics to evaluate, ex ante, the desirability of alternate data structures. Organizations can use these evaluations to enhance the efficient and effective retrieval of information by creating data structures that minimize end user query complexity.

Feeding strategies for grain-fed cattle in a hot environment

Six Bos taurus (Hereford) steers (body weight 324 22 kg) were used in a 45-day study with a replicated 3 x 3 Latin-square design. Three treatments [ad libitum feeding (ADLIB); limit feeding, 85% of ad libitum (LIMIT); bunk management feeding where steers were only given access to feed from 1600 to 0800 hours the following day (BUNK)] were imposed over 3 periods, with 2 steers assigned to each treatment in each period. Cattle were managed in a temperature-controlled metabolism unit and were exposed to both thermoneutral (17.7degreesC-26.1degreesC) and hot (16.7degreesC-32.9degreesC) environmental conditions. By design, during the thermoneutral period, the ADLIB cattle displayed greater intake (P < 0.05) than the LIMIT group, with the BUNK group being intermediate. However, during the hot period, both the LIMIT and BUNK treatment groups increased feed intake 4-5%, whereas feed intake of the ADLIB treatment group declined nearly 2%. During both periods respiration rate (RR, breath/min) followed the same pattern that was observed for feed intake, with the greatest (P < 0.05) RR found in the ADLIB treatment group (81.09 and 109.55, thermoneutral and hot, respectively) and lowest (P < 0.05) RR in the LIMIT treatment group (74.47 and 102.76, thermoneutral and hot, respectively). Rectal temperature (RT) did not differ among treatments during the thermoneutral period or the first hot day, although during the thermoneutral period the ADLIB treatment group did tend to display a lower RT, possibly as a result of other physiological processes (pulse rate and RR) aiding to keep RT lower. During the hot period, differences in RT were found on Day 5, with the LIMIT cattle having lower (P < 0.10) RT (38.92degreesC) than the ADLIB (39.18degreesC) cattle, with BUNK cattle RT (39.14degreesC) being intermediate. However, when hourly data were examined, the ADLIB cattle had greater(P < 0.05) RT than the BUNK and LIMIT at 1800 hours and greater RT (P < 0.05) than the LIMIT group at 1400, 1500, and 1600 hours. Clearly, a change in diurnal RT pattern was obtained by using the LIMIT and BUNK feeding regimen. Both of these groups displayed a peak RT during the hot conditions, between 2100 and 2200 hours, whereas the ADLIB group displayed a peak RT between 1400 and 1500 hours, a time very close to when peak climatic stress occurs. Based on these results it is apparent that feedlot managers could alleviate the effects of adverse hot weather on cattle by utilising either a limit-feeding regimen or altering bunk management practices to prevent feed from being consumed several hours prior to the hottest portion of the day.

Poverty and the economic effects of TB in rural China

OBJECTIVE: To investigate the economic effects of illness on individual tuberculosis (TB) cases in rural China and to use a case-control study to show a strong TB-poverty link. SETTING: In 2002-2004 we studied 160 new smear-positive pulmonary tuberculosis (PTB) cases and 320 age- and sex-matched controls living in neighbouring houses in four rural counties of Henan Province. DESIGN: Cases and controls were interviewed 1-3 months after patients were diagnosed. We used matched multivariate logistic regression to compare cases with controls for poverty status using household income, household assets and relative wealth within the village. We conducted follow-up interviews of patients 10-12 months later to assess economic effects by collecting data on treatment costs, income losses, coping strategies and treatment completion. RESULTS: Poverty is strongly associated with TB incidence even after controlling for smoking and other risk factors. Excluding income losses, direct out-of-pocket treatment costs (medical and non-medical) accounted for 55.5 % of average annual household income, and most TB cases fell into heavy debt. The DOTS cure rate was 91 %. When DOTS was incomplete or not done, mortality was high. CONCLUSIONS: Poverty is both a cause and a devastating outcome of TB. Ongoing poverty reduction schemes in China must also include reducing TB.

Risk of serious NSAID-related gastrointestinal events during long-term exposure: a systematic review

Objective: Exposure to non-steroidal anti-inflammatory drugs (NSAIDs) is associated wit increased risk of serious gastrointestinal (GI) events compared with non-exposure. We investigated whether that risk is sustained over time. Data sources: Cochrane Controlled Trials Register (to 2002); MEDLINE, EMBASE, Derwent Drug File and Current Contents (1999-2002); manual searching of reviews (1999-2002). Study selection: From 479 search results reviewed and 221 articles retrieved, seven studies of patients exposed to prescription non-selective NSAIDs for more than 6 months and reporting time-dependent serious GI event rates were selected for quantitative data synthesis. These were stratified into two groups by study design. Data extraction: Incidence of GI events and number of patients at specific time points were extracted. Data synthesis: Meta-regression analyses were performed. Change in risk was evaluated by testing whether the slope of the regression line declined over time. Four randomised controlled trials (RCTs) provided evaluable data from five NSAID arms (aspirin, naproxen, two ibuprofen arms, and diclofenac). When the RCT data were combined, a small significant decline in annualised risk was seen: -0.005% (95% Cl, -0.008% to -0.001%) per month. Sensitivity analyses were conducted because there was disparity within the RCT data. The pooled estimate from three cohort studies showed no significant decline in annualised risk over periods up to 2 years: -0.003% (95% Cl, -0.008% to 0.003%) per month. Conclusions: Small decreases in risk over time were observed; these were of negligible clinical importance. For patients who need long-term (> 6 months) treatment, precautionary measures should be considered to reduce the net probability of serious GI events over the anticipated treatment duration. The effect of intermittent versus regular daily therapy on long-term risk needs further investigation.

Use of latent profile analysis to identify eating disorder phenotypes in an adult Australian twin cohort

Context: The relationships among the different eating disorders that exist in the community are poorly understood, especially for residual disorders in which bingeing or purging occurs in the absence of other behaviors. Objective: To examine a community sample for the number of mutually exclusive weight and eating profiles. Design: Data regarding lifetime eating disorder symptoms and weight range were submitted to a latent profile analysis. Profiles were compared regarding personality, current eating and weight, retrospectively reported life events, and lifetime depressive psychopathology. Setting: Longitudinal study among female twins from the Australian Twin Registry in whom eating was assessed by a telephone interview. Participants: A community sample of 1002 twins (individuals) who had participated in earlier waves of data collection. Main Outcome Measures: Number and clinical character of latent profiles. Results: The best fit was a 5-profile solution with women who were (1) of normal weight with few lifetime eating disorders (4.3%), (2) overweight (10.6% had a lifetime eating disorder), (3) underweight and generally had no eating disorders except for 5.3% who had restricting anorexia nervosa, (4) of low to normal weight (89.0% had a lifetime eating disorder), and (5) obese (37.0% had a lifetime eating disorder). Each profile contained more than 1 type of lifetime eating disorder except for the third profile. Women in the first and third profiles had the best functioning, with women in the fourth and fifth profiles having similarly poorer functioning. The women in the fourth group had a symptom profile distinctive from the other 4 groups in terms of severity; they were also more likely to have had lifetime major depression and suicidality. Conclusion: Lifetime weight ranges and the severity of eating disorder symptoms affected clustering more than the type of eating disorder symptom.

On aggregation issues in spatial data management

Large amounts of information can be overwhelming and costly to process, especially when transmitting data over a network. A typical modern Geographical Information System (GIS) brings all types of data together based on the geographic component of the data and provides simple point-and-click query capabilities as well as complex analysis tools. Querying a Geographical Information System, however, can be prohibitively expensive due to the large amounts of data which may need to be processed. Since the use of GIS technology has grown dramatically in the past few years, there is now a need more than ever, to provide users with the fastest and least expensive query capabilities, especially since an approximated 80 % of data stored in corporate databases has a geographical component. However, not every application requires the same, high quality data for its processing. In this paper we address the issues of reducing the cost and response time of GIS queries by preaggregating data by compromising the data accuracy and precision. We present computational issues in generation of multi-level resolutions of spatial data and show that the problem of finding the best approximation for the given region and a real value function on this region, under a predictable error, in general is "NP-complete.