Patterns and correlates of self-reported racial discrimination among Australian Aboriginal and Torres Strait Islander adults, 2008–09: analysis of national survey data

Background
There is now considerable evidence that racism is a pernicious and enduring social problem with a wide range of detrimental outcomes for individuals, communities and societies. Although indigenous people worldwide are subjected to high levels of racism, there is a paucity of population-based, quantitative data about the factors associated with their reporting of racial discrimination, about the settings in which such discrimination takes place, and about the frequency with which it is experienced. Such information is essential in efforts to reduce both exposure to racism among indigenous people and the harms associated with such exposure.

Methods
Weighted data on self-reported racial discrimination from over 7,000 Indigenous Australian adults participating in the 2008–09 National Aboriginal and Torres Strait Islander Survey, a nationally representative survey conducted by the Australian Bureau of Statistics, were analysed by socioeconomic, demographic and cultural factors.

Results
More than one in four respondents (27%) reported experiencing racial discrimination in the past year. Racial discrimination was most commonly reported in public (41% of those reporting any racial discrimination), legal (40%) and work (30%) settings. Among those reporting any racial discrimination, about 40% experienced this discrimination most or all of the time (as opposed to a little or some of the time) in at least one setting. Reporting of racial discrimination peaked in the 35–44 year age group and then declined. Higher reporting of racial discrimination was associated with removal from family, low trust, unemployment, having a university degree, and indicators of cultural identity and participation. Lower reporting of racial discrimination was associated with home ownership, remote residence and having relatively few Indigenous friends.

Conclusions
These data indicate that racial discrimination is commonly experienced across a wide variety of settings, with public, legal and work settings identified as particularly salient. The observed relationships, while not necessarily causal, help to build a detailed picture of self-reported racial discrimination experienced by Indigenous people in contemporary Australia, providing important evidence to inform anti-racism policy.

Hybrid approach to ensure data confidentiality and tampered data recovery for RFID tag

Radio Frequency Identification (RFID) is an emerging wireless object identification technology with many potential applications such as supply chain management, personnel tracking and healthcare. However, security vulnerabilities of the RFID system have been a serious concern for its wide adoption in many applications. Although there are lots of work to provide privacy and anonymity, little focus has been given to ensure confidentiality and integrity of RFID tag data. To this end, we propose a lightweight hybrid approach based on stenographic and watermarking to ensure data confidentiality, linkability resistance and integrity on the RFID tags data. The proposed technique is capable of tampered data recovering and restoring for RFID tag. It has been validated and tested on EPC class 1 gen2 tags.

Improvement of polypyrrole coating adhesion by radio frequency plasma

Tariq worked in the area of electronic textiles. He coated polyester fabric and PVDF films with polypyrrole. Plasma treatment was used to improve binding of coatings over the surface. He investigated in detail, the factors responsible for adhesion improvement using XPS, AFM, SEM, contact angle, abrasion tests and conductivity measurements. Different plasma gases, plasma power and plasma modes were investigated to get optimum bonding data. His investigations pointed towards improved surface oxygen functionalization and suitable surface morphology for improved bonding.

Determinants of the frequency of contact lens wear

To characterize and discover the determinants of the frequency of wear (FOW) of contact lenses. Survey forms were sent to contact lens fitters in up to 40 countries between January and March every year for 5 consecutive years (2007–2011). Practitioners were asked to record data relating to the first 10 contact lens fits or refits performed after receiving the survey form. Only data for daily wear lens fits were analyzed. Data were collected in relation to 74,510 and 9,014 soft and rigid lens fits, respectively. Overall, FOW was 5.9±1.7 days per week (DPW). When considering the proportion of lenses worn between one to seven DPW, the distribution for rigid lenses is skewed toward full-time wear (7 DPW), whereas the distribution for soft daily disposable lenses is perhaps bimodal, with large and small peaks at seven and two DPW, respectively. There is a significant variation in FOW among nations (P<0.0001), ranging from 6.8±1.0 DPW in Greece to 5.1±2.5 DPW in Kuwait. For soft lenses, FOW increases with decreasing age. Females (6.0±1.6 DPW) wear lenses more frequently than males (5.8±1.7 DPW) (P=0.0002). FOW is greater among those wearing presbyopic corrections (6.1±1.4 DPW) compared with spherical (5.9±1.7 DPW) and toric (5.9±1.6 DPW) designs (P<0.0001). FOW with hydrogel peroxide systems (6.4±1.1 DPW) was greater than that with multipurpose systems (6.2±1.3 DPW) (P<0.0001).

Medication errors in ED: do patient characteristics and the environment influence the nature and frequency of medication errors?

Background: Medication safety is of increasing importance and understanding the nature and frequency of medication errors in the Emergency Department (ED) will assist in tailoring interventions which will make patient care safer. The challenge with the literature to date is the wide variability in the frequency of errors reported and the reliance on incident reporting practices of busy ED staff. Methods: A prospective, exploratory descriptive design using point prevalence surveys was used to establish the frequency of observed medication errors in the ED. In addition, data related to contextual factors such as ED patients, staffing and workload were also collected during the point prevalence surveys to enable the analysis of relationships between the frequency and nature of specific error types and patient and ED characteristics at the time of data collection. Results: A total of 172 patients were included in the study: 125 of whom patients had a medication chart. The prevalence of medication errors in the ED studied was 41.2% for failure to apply patient ID bands, 12.2% for failure to document allergy status and 38.4% for errors of omission. The proportion of older patients in the ED did not affect the frequency of medication errors. There was a relationship between high numbers of ATS 1, 2 and 3 patients (indicating high levels of clinical urgency) and increased rates of failure to document allergy status. Medication errors were affected by ED occupancy, when cubicles in the ED were over 50% occupied, medication errors occurred more frequently. ED staffing affects the frequency of medication errors, there was an increase in failure to apply ID bands and errors of omission when there were unfilled nursing deficits and lower levels of senior medical staff were associated with increased errors of omission. Conclusions: Medication errors related to patient identification, allergy status and medication omissions occur more frequently in the ED when the ED is busy, has sicker patients and when the staffing is not at the minimum required staffing levels.

Frequency-domain beamformers using conjugate gradient techniques for speech enhancement

A multiple-iteration constrained conjugate gradient (MICCG) algorithm and a single-iteration constrained conjugate gradient (SICCG) algorithm are proposed to realize the widely used frequency-domain minimum-variance-distortionless-response (MVDR) beamformers and the resulting algorithms are applied to speech enhancement. The algorithms are derived based on the Lagrange method and the conjugate gradient techniques. The implementations of the algorithms avoid any form of explicit or implicit autocorrelation matrix inversion. Theoretical analysis establishes formal convergence of the algorithms. Specifically, the MICCG algorithm is developed based on a block adaptation approach and it generates a finite sequence of estimates that converge to the MVDR solution. For limited data records, the estimates of the MICCG algorithm are better than the conventional estimators and equivalent to the auxiliary vector algorithms. The SICCG algorithm is developed based on a continuous adaptation approach with a sample-by-sample updating procedure and the estimates asymptotically converge to the MVDR solution. An illustrative example using synthetic data from a uniform linear array is studied and an evaluation on real data recorded by an acoustic vector sensor array is demonstrated. Performance of the MICCG algorithm and the SICCG algorithm are compared with the state-of-the-art approaches.

Self-reported risk-taking behavior during matched-frequency sessions of alcohol versus combined alcohol and energy drinks consumption: Does co-ingestion increase risk-taking?

Background: Emerging evidence indicates that consumers of alcohol mixed with energy drink (AmED) self-report lower odds of risk-taking after consuming AmED versus alcohol alone. However, these studies have been criticized for failing to control for relative frequency of AmED versus alcohol-only consumption sessions. These studies also do not account for quantity of consumption and general alcohol-related risk-taking propensity. The aims of the present study were to (i) compare rates of risk-taking in AmED versus alcohol sessions among consumers with matched frequency of use and (ii) identify consumption and person characteristics associated with risk-taking behavior in AmED sessions. Methods: Data were extracted from 2 Australian community samples and 1 New Zealand community sample of AmED consumers (n = 1,291). One-fifth (21%; n = 273) reported matched frequency of AmED and alcohol use. Results: The majority (55%) of matched-frequency participants consumed AmED and alcohol monthly or less. The matched-frequency sample reported significantly lower odds of engaging in 18 of 25 assessed risk behaviors in AmED versus alcohol sessions. Similar rates of engagement were evident across session type for the remaining behaviors, the majority of which were low prevalence (reported by <15%). Regression modeling indicated that risk-taking in AmED sessions was primarily associated with risk-taking in alcohol sessions, with increased average energy drink (ED) intake associated with certain risk behaviors (e.g., being physically hurt, not using contraception, and driving while over the legal alcohol limit). Conclusions: Bivariate analyses from a matched-frequency sample align with past research showing lower odds of risk-taking behavior after AmED versus alcohol consumption for the same individuals. Multivariate analyses showed that risk-taking in alcohol sessions had the strongest association with risk-taking in AmED sessions. However, hypotheses of increased risk-taking post-AmED consumption were partly supported: Greater ED intake was associated with increased likelihood of specific behaviors, including drink-driving, sexual behavior, and aggressive behaviors in the matched-frequency sample after controlling for alcohol intake and risk-taking in alcohol sessions. These findings highlight the need to consider both personal characteristics and beverage effects in harm reduction strategies for AmED consumers.

Adolescent substance use and educational attainment: an integrative data analysis comparing cannabis and alcohol from three Australasian cohorts

BACKGROUND: The relative contributions of cannabis and alcohol use to educational outcomes are unclear. We examined the extent to which adolescent cannabis or alcohol use predicts educational attainment in emerging adulthood. METHODS: Participant-level data were integrated from three longitudinal studies from Australia and New Zealand (Australian Temperament Project, Christchurch Health and Development Study, and Victorian Adolescent Health Cohort Study). The number of participants varied by analysis (N=2179-3678) and were assessed on multiple occasions between ages 13 and 25. We described the association between frequency of cannabis or alcohol use prior to age 17 and high school non-completion, university non-enrolment, and degree non-attainment by age 25. Two other measures of alcohol use in adolescence were also examined. RESULTS: After covariate adjustment using a propensity score approach, adolescent cannabis use (weekly+) was associated with 1½ to two-fold increases in the odds of high school non-completion (OR=1.60, 95% CI=1.09-2.35), university non-enrolment (OR=1.51, 95% CI=1.06-2.13), and degree non-attainment (OR=1.96, 95% CI=1.36-2.81). In contrast, adjusted associations for all measures of adolescent alcohol use were inconsistent and weaker. Attributable risk estimates indicated adolescent cannabis use accounted for a greater proportion of the overall rate of non-progression with formal education than adolescent alcohol use. CONCLUSIONS: Findings are important to the debate about the relative harms of cannabis and alcohol use. Adolescent cannabis use is a better marker of lower educational attainment than adolescent alcohol use and identifies an important target population for preventive intervention.

A differentially private algorithm for location data release

The rise of mobile technologies in recent years has led to large volumes of location information, which are valuable resources for knowledge discovery such as travel patterns mining and traffic analysis. However, location dataset has been confronted with serious privacy concerns because adversaries may re-identify a user and his/her sensitivity information from these datasets with only a little background knowledge. Recently, several privacy-preserving techniques have been proposed to address the problem, but most of them lack a strict privacy notion and can hardly resist the number of possible attacks. This paper proposes a private release algorithm to randomize location dataset in a strict privacy notion, differential privacy, with the goal of preserving users’ identities and sensitive information. The algorithm aims to mask the exact locations of each user as well as the frequency that the user visits the locations with a given privacy budget. It includes three privacy-preserving operations: private location clustering shrinks the randomized domain and cluster weight perturbation hides the weights of locations, while private location selection hides the exact locations of a user. Theoretical analysis on privacy and utility confirms an improved trade-off between privacy and utility of released location data. Extensive experiments have been carried out on four real-world datasets, GeoLife, Flickr, Div400 and Instagram. The experimental results further suggest that this private release algorithm can successfully retain the utility of the datasets while preserving users’ privacy.

Predictive data mining for converged internet of things: a mobile health perspective

Mobile Health (mHealth) is now emerging with Internet of Things (IoT), Cloud and big data along with the prevalence of smart wearable devices and sensors. There is also the emergence of smart environments such as smart homes, cars, highways, cities, factories and grids. Presently, it is difficult to quickly forecast or prevent urgent health situations in real-time as health data are analyzed offline by a physician. Sensors are expected to be overloaded by demands of providing health data from IoT networks and smart environments. This paper proposes to resolve the problems by introducing an inference system so that life-threatening situations can be prevented in advance based on a short and long term health status prediction. This prediction is inferred from personal health information that is built by big data in Cloud. The inference system can also resolve the problem of data overload in sensor nodes by reducing data volume and frequency to reduce workload in sensor nodes. This paper presents a novel idea of tracking down and predicting a personal health status as well as intelligent functionality of inference in sensor nodes to interface IoT networks

A Spatial-Temporal Downscaling Approach To Construction Of Rainfall Intensity-Duration-Frequency Relations In The Context Of Climate Change

This paper proposes a spatial-temporal downscaling approach to construction of the intensity-duration-frequency (IDF) relations at a local site in the context of climate change and variability. More specifically, the proposed approach is based on a combination of a spatial downscaling method to link large-scale climate variables given by General Circulation Model (GCM) simulations with daily extreme precipitations at a site and a temporal downscaling procedure to describe the relationships between daily and sub-daily extreme precipitations based on the scaling General Extreme Value (GEV) distribution. The feasibility and accuracy of the suggested method were assessed using rainfall data available at eight stations in Quebec (Canada) for the 1961-2000 period and climate simulations under four different climate change scenarios provided by the Canadian (CGCM3) and UK (HadCM3) GCM models. Results of this application have indicated that it is feasible to link sub-daily extreme rainfalls at a local site with large-scale GCM-based daily climate predictors for the construction of the IDF relations for present (1961-1990) and future (2020s, 2050s, and 2080s) periods at a given site under different climate change scenarios. In addition, it was found that annual maximum rainfalls downscaled from the HadCM3 displayed a smaller change in the future, while those values estimated from the CGCM3 indicated a large increasing trend for future periods. This result has demonstrated the presence of high uncertainty in climate simulations provided by different GCMs. In summary, the proposed spatial-temporal downscaling method provided an essential tool for the estimation of extreme rainfalls that are required for various climate-related impact assessment studies for a given region.

Análise do efeito de polimorfismos não-sinônimos em genes de reparo de DNA da via BER na resposta inflamatória da meningite

In vitro and in animal models, APE1, OGG1, and PARP-1 have been proposed as being involved with inflammatory response. In this work, we have investigated if the SNPs APE1 Asn148Glu, OGG1 Ser326Cys, and PARP-1 Val762Ala are associated to meningitis and also developed a system to enable the functional analysis of polymorphic proteins. Patients with bacterial meningitis (BM), aseptic meningitis (AM) and controls (non-infected) genotypes were investigated by PIRA-PCR or PCR-RFLP. DNA damages were detected in genomic DNA by Fpg treatment. IgG and IgA were measured from plasma and the cytokines and chemokines were measured from cerebrospinal fluid samples using Bio-Plex assays. The levels of NF-κB and c-Jun were measured in CSF by dot blot assays. A significant (P<0.05) increase in the frequency of APE1 148Glu allele in BM and AM patients was observed. A significant increase in the genotypes Asn/Asn in control group and Asn/Glu in BM group was also found. For the SNP OGG1 Ser326Cys, the genotype Cys/Cys was more frequent (P<0.05) in BM group. The frequency of PARP-1 Val/Val genotype was higher in control group (P<0.05). The occurrence of combined SNPs increased significantly in BM patients, indicating that these SNPs may be associated to the disease. Increasing in sensitive sites to Fpg was observed in carriers of APE1 148Glu allele or OGG1 326Cys allele, suggesting that SNPs affect DNA repair activity. Alterations in IgG production were observed in the presence of SNPs APE1Asn148Glu, OGG1Ser326Cys or PARP-1Val762Ala. Reductions in the levels ofIL-6, IL-1Ra, MCP-1/CCL2and IL-8/CXCL8 were observed in the presence of APE1148Glu allele in BM patients, however no differences were observed in the levels of NF-κB and c-Jun considering genotypes and analyzed groups. Using APE1 as model, a system to enable the analysis of cellular effects and functional characterization of polymorphic proteins was developed using strategies of cloning APE1 cDNA in pIRES2-EGFP vector, cellular transfection of the construction obtained, siRNA for endogenous APE1 and cellular cultures genotyping. In conclusion, we obtained evidences of an effect of SNPs in DNA repair genes on the regulation of immune response. This is a pioneering work in the field that shows association of BER variant enzymes with an infectious disease in human patients, suggesting that the SNPs analyzed may affect immune response and damage by oxidative stress level during brain infection. Considering these data, new approaches of functional characterization must be developed to better analysis and interactions of polymorphic proteins in response to this context

Feeding level and frequency for freshwater angelfish

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Assessment of DGAT1 and LEP gene polymorphisms in three Nelore (Bos indicus) lines selected for growth and their relationship with growth and carcass traits

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The wavelet method as an alternative for reducing ionospheric effects from single-frequency GPS receivers

The ionospheric effect is one of the major errors in GPS data processing over long baselines. As a dispersive medium, it is possible to compute its influence on the GPS signal with the ionosphere-free linear combination of L1 and L2 observables, requiring dual-frequency receivers. In the case of single-frequency receivers, ionospheric effects are either neglected or reduced by using a model. In this paper, an alternative for single-frequency users is proposed. It involves multiresolution analysis (MRA) using a wavelet analysis of the double-difference observations to remove the short- and medium-scale ionosphere variations and disturbances, as well as some minor tropospheric effects. Experiments were carried out over three baseline lengths from 50 to 450 km, and the results provided by the proposed method were better than those from dual-frequency receivers. The horizontal root mean square was of about 0.28 m (1 sigma).