From food to offspring down : tissue-specific discrimination and turn-over of stable isotopes in herbivorous waterbirds and other avian foraging guilds

Isotopic discrimination and turn-over are fundamental to the application of stable isotope ecology in animals. However, detailed information for specific tissues and species are widely lacking, notably for herbivorous species. We provide details on tissue-specific carbon and nitrogen discrimination and turn-over times from food to blood, feathers, claws, egg tissues and offspring down feathers in four species of herbivorous waterbirds. Source-to-tissue discrimination factors for carbon (δ¹³C) and nitrogen stable isotope ratios (δ¹⁵N) showed little variation across species but varied between tissues. Apparent discrimination factors ranged between −0.5 to 2.5‰ for δ¹³C and 2.8 to 5.2‰ for δ¹⁵N, and were more similar between blood components than between keratinous tissues or egg tissue. Comparing these results with published data from other species we found no effect of foraging guild on discrimination factors for carbon but a significant foraging-guild effect for nitrogen discrimination factors.

Turn-over of δ¹³C in tissues was most rapid in blood plasma, with a half-life of 4.3 d, whereas δ¹³C in blood cells had a half-life of approximately 32 d. Turn-over times for albumen and yolk in laying females were similar to those of blood plasma, at 3.2 and 6.0 d respectively. Within yolk, we found decreasing half-life times of δ¹³C from inner yolk (13.3 d) to outer yolk (3.1 d), related to the temporal pattern of tissue formation.

We found similarities in tissue-specific turn-over times across all avian species studied to date. Yet, while generalities regarding discrimination factors and tissue turn-over times can be made, a large amount of variation remains unexplained.

DDoS discrimination by linear discriminant analysis (LDA)

In this paper, we propose an effective approach with a supervised learning system based on Linear Discriminant Analysis (LDA) to discriminate legitimate traffic from DDoS attack traffic. Currently there is a wide outbreak of DDoS attacks that remain risky for the entire Internet. Different attack methods and strategies are trying to challenge defence systems. Among the behaviours of attack sources, repeatable and predictable features differ from source of legitimate traffic. In addition, the DDoS defence systems lack the learning ability to fine-tune their accuracy. This paper analyses real trace traffic from publicly available datasets. Pearson's correlation coefficient and Shannon's entropy are deployed for extracting dependency and predictability of traffic data respectively. Then, LDA is used to train and classify legitimate and attack traffic flows. From the results of our experiment, we can confirm that the proposed discrimination system can differentiate DDoS attacks from legitimate traffic with a high rate of accuracy.

Feedback reporting of survey data to healthcare aides

Background

This project occurred during the course of the Translating Research in Elder Care (TREC) program of research. TREC is a multilevel and longitudinal research program being conducted in the three Canadian Prairie Provinces of Alberta, Saskatchewan, and Manitoba. The main purpose of TREC is to increase understanding about the role of organizational context in influencing knowledge use in residential long-term care settings. The purpose of this study was to evaluate healthcare aides’ (HCAs) perceptions of a one-page poster designed to feed back aggregated data (including demographic information and perceptions about influences on best practice) from the TREC survey they had recently completed.

Methods
A convenience sample of 7 of the 15 nursing homes participating in the TREC research program in Alberta were invited to participate. Specific facility-level summary data were provided to each facility in the form of a one-page poster report. Two weeks following delivery of the report, a convenience sample of HCAs was surveyed using one-to-one structured interviews.

Results
One hundred twenty-three HCAs responded to the evaluation survey. Overall, HCAs’ opinions about presentation of the feedback report and the understandability, usability, and usefulness of the content were positive. For each report, analysis of data and production and inspection of the report took up to one hour. Information sessions to introduce and explain the reports averaged 18 minutes. Two feedback reports (minimum) were supplied to each facility at a cost of CAN$2.39 per report, for printing and laminating.

Conclusions
This study highlights not only the feasibility of producing understandable, usable, and useful feedback reports of survey data but also the value and importance of providing feedback to survey respondents. More broadly, the findings suggest that modest strategies may have a positive and desirable effect in participating sites.

Age discrimination in the evaluation of job applicants

This study investigated the nature of age discrimination against older job applicants. One hundred fifty-six participants (102 students; 54 organization based) evaluated a hypothetical job applicant's (aged 33–66 years) work-related competences and likelihood of being hired. Applicant age affected hiring decisions for both samples where there was a preference for hiring applicants aged 42–48 years. Applicants at both the older and younger ends of the continuum were less likely to be hired, with the oldest applicants (over 54 years) being the least likely to be hired. Although the applicants' age negatively affected evaluations of their trainability and sociability, the effect of applicant age on hiring evaluations was not mediated by these work-related competencies, suggesting that age discrimination occurs via direct bias against older workers.

Unfair punishment : when criminal record checks lead to discrimination

Applying for a job is stressful enough, but if you have a criminal record, even if it’s not relevant to the job you’re applying for, it can be a nightmare.

Employers in Australia regularly discriminate on the grounds that a person has an irrelevant criminal record and checking criminal records is on the increase. The number of criminal record checks undertaken in Victoria have risen by almost 6,000% since 1993.

It is concerning then that the few laws that prohibit discrimination on the basis of irrelevant criminal record lack real teeth.

Perceived discrimination and stigmatisation against severely obese women : age and weight loss make a difference

Aims: Patients’ perceptions about weight-related stigma and discrimination were assessed in 2 groups of patients, obese and laparoscopic adjustable gastric banding (LAGB).

Methods: Seven focus group sessions were held including a total of 32 women, 8 obese (body mass index 35+) and 24 who had lost 50% of excess weight following bariatric surgery. During the sessions, participants were asked to consider their experiences in situations including general, family, friends, work place, medical, and educational settings.

Results: Whilst perceptions of discrimination and stigmatisation were common and affected many life situations, they were less prevalent than previous reports. It appeared that it was not the frequency or number of events which affected an individual but the intensity of the experience. Younger women reported greater discrimination than older women and felt the social consequences of obesity to a greater extent. Older women were more concerned about the consequences of being overweight on their health.

Conclusions: Women who had lost weight considered that aspects of their own behaviours when obese contributed to their experiences of discrimination and stigmatisation. Perceptions of discrimination and stigmatisation appear to be influenced by age and current weight status.

Unsupervised DRG upcoding detection in healthcare databases

Diagnosis Related Group (DRG) upcoding is an anomaly in healthcare data that costs hundreds of millions of dollars in many developed countries. DRG upcoding is typically detected through resource intensive auditing. As supervised modeling of DRG upcoding is severely constrained by scope and timeliness of past audit data, we propose in this paper an unsupervised algorithm to filter data for potential identification of DRG upcoding. The algorithm has been applied to a hip replacement/revision dataset and a heart-attack dataset. The results are consistent with the assumptions held by domain experts.

Visualising a state-wide patient data collection : a case study to expand the audience for healthcare data

This paper describes the application of existing and novel adaptations of visualisation techniques to routinely collected health data. The aim of this case study is to examine the capacity for visualisation approaches to quickly and e ectively inform clinical, policy, and scal decision making to improve healthcare provision. We demonstrate the use of interactive graphics, fluctuation plots, mosaic plots, time plots, heatmaps, and disease maps to visualise patient admission, transfer, in-hospital mortality, morbidity coding, execution of diagnosis and treatment guidelines, and the temporal and spatial variations of diseases. The relative e ectiveness of these techniques and associated challenges are discussed.

Is chemotherapy dose intensity adequate in breast cancer management in the Australian healthcare setting: a retrospective analysis

Aim
To determine the adequacy of chemotherapy received dose intensity (RDI) in breast cancer treatment in a general population and to identify factors that influence RDI.

Methods
A retrospective analysis of breast cancer patients who commenced a course of i.v. chemotherapy in 2008 was undertaken. Data were collected on patient and tumor characteristics, chemotherapy regimen, dose (including delays, reductions and the reasons for these), granulocyte colony-stimulating factor (G-CSF) use and febrile neutropenia incidence. RDI was calculated using the planned and actual dose received and time taken. A level of ≥85% RDI was considered acceptable for treatment given with curative intent.

Results
In all, 131 patients (aged 28 to 77 years) received chemotherapy in adjuvant (n = 76, 58%), neoadjuvant (n = 11, 8%) and metastatic settings (n = 44, 34%). RDI did not reach 85% for 12% adjuvant, 36% neoadjuvant and 34% metastatic cases (χ2 = 10.55, P = 0.005). Overall, 43% of patients received G-CSF.

Conclusion
Acceptable chemotherapy RDI was delivered for most patients in the adjuvant setting but not in the neoadjuvant setting. G-CSF treatment contributed to the optimization of dose intensity in the adjuvant setting only. Dose intensity in the metastatic setting was considered satisfactory where quality of life is the primary focus. Other factors can be modified to improve RDI.

Utilising self-report data to measure racial discrimination in the labour market

Although economists have developed a series of approaches to modelling the existence of labour market discrimination, rarely is this topic examined by analysing self-report survey data. After reviewing theories and empirical models of labour market discrimination, we examine self-reported experience of discrimination at different stages in the labour market, among three racial groups utilising U.S. data from the 2001-2003 National Survey of American Life. Our findings indicate that African Americans and Caribbean blacks consistently report more experience of discrimination in the labour market than their non-Hispanic white counterparts. At different stages of the labour market, including hiring, termination and promotion, these groups are more likely to report discrimination than non-Hispanic whites. After controlling for social desirability bias and several human capital and socio-demographic covariates, the results remain robust for African Americans. However, the findings for Caribbean blacks were no longer significant after adjusting for social desirability bias. Although self-report data is rarely utilised to assess racial discrimination in labour economics, our study confirms the utility of this approach as demonstrated in similar research from other disciplines. Our results indicate that after adjusting for relevant confounders self-report survey data is a viable approach to estimating racial discrimination in the labour market. Implications of the study and directions for future research are provided.

Labour market and other discrimination facing Indigenous Australian

This paper uses self-reported data to illustrate how Indigenous Australians experience discrimination and how it is potentially associated with poor labour market outcomes. After giving consideration to what factors may lead people to report being discriminated against, an empirical analysis of self-reported discrimination is presented, utilising data from the 2008 National Aboriginal and Torres Strait Islander Social Survey (NATSISS). Correlations between discrimination experienced in different settings are identified, and the association of discrimination with human capital and other characteristics is presented. The results suggest that the main process driving the reporting of discrimination is the extent to which an individual is exposed to situations in which they interact with potential discriminators. This could mean that some Indigenous Australians decrease their labour supply in order to avoid potentially adverse (discriminatory) situations. Implications for understanding Indigenous disadvantage are discussed along with recommendations for both addressing discrimination and enhancing the resilience of individuals facing discrimination.