Glutamine repeat variants in human RUNX2 associated with decreased femoral neck BMD, broadband ultrasound attenuation and target gene transactivation

RUNX2 is an essential transcription factor required for skeletal development and cartilage formation. Haploinsufficiency of RUNX2 leads to cleidocranial displaysia (CCD) a skeletal disorder characterised by gross dysgenesis of bones particularly those derived from intramembranous bone formation. A notable feature of the RUNX2 protein is the polyglutamine and polyalanine (23Q/17A) domain coded by a repeat sequence. Since none of the known mutations causing CCD characterised to date map in the glutamine repeat region, we hypothesised that Q-repeat mutations may be related to a more subtle bone phenotype. We screened subjects derived from four normal populations for Q-repeat variants. A total of 22 subjects were identified who were heterozygous for a wild type allele and a Q-repeat variant allele: (15Q, 16Q, 18Q and 30Q). Although not every subject had data for all measures, Q-repeat variants had a significant deficit in BMD with an average decrease of 0.7SD measured over 12 BMD-related parameters (p = 0.005). Femoral neck BMD was measured in all subjects (−0.6SD, p = 0.0007). The transactivation function of RUNX2 was determined for 16Q and 30Q alleles using a reporter gene assay. 16Q and 30Q alleles displayed significantly lower transactivation function compared to wild type (23Q). Our analysis has identified novel Q-repeat mutations that occur at a collective frequency of about 0.4%. These mutations significantly alter BMD and display impaired transactivation function, introducing a new class of functionally relevant RUNX2 mutants.

Multi-target tracking via space transformations using a single frequency continuous wave radar

This paper investigates the location and velocity estimation problem involving multiple targets using the phase difference and frequency shift of the returned Doppler modulated signal. The minimal receiver configuration that addresses the data association and missing information problem is presented for the case of linear arrays. Non-linearly modeled Doppler radar measurements are used to obtain an accurate estimate of the target dynamics progressively in a linear framework utilizing a recently developed robust state estimation approach.

StenoCipher to provide 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 much work has been done to provide privacy and anonymity, little focus has been given to ensure RFID data confidentiality, integrity and to address the tampered data recovery problem. To this end, we propose a lightweight stenographic-based approach to ensure RFID data confidentiality and integrity as well as the recovery of tampered RFID data.

Enhancing RFID data quality and reliability

This thesis addressed the problem of data quality, reliability and energy consumption of networked Radio Frequency Identification systems for business intelligence applications decision making processes. The outcome of the research substantially improved the accuracy and reliability of RFID generated data as well as energy depletion thus prolonging RFID system lifetime.

DSM-5 mixed specifier for manic episodes: evaluating the effect of depressive features on severity and treatment outcome using asenapine clinical trial data

Background:
To describe the frequency of mixed specifier as proposed in DSM-5 in bipolar I patients with manic episodes, and to evaluate the effect of mixed specifier on symptom severity and treatment outcome.

Methods:
This post-hoc analysis used proxies for DSM-5 mixed features specifier by using MADRS or PANSS items.

Results:
Of the 960 patients analysed, 34%, 18% and 4.3% of patients, respectively, had ≥3 depressive features with mild (score ≥1 for MADRS items and ≥2 for PANSS item), moderate (score ≥2 MADRS, ≥3 PANSS) and severe (score ≥3 MADRS, ≥4 PANSS) symptoms. In patients with ≥3 depressive features and independent of treatment: MADRS remission (score ≤12) rate decreased with increasing severity (61–43%) and YMRS remission (score ≤12) was similar for mild and moderate patients (36–37%), but higher for severe (54%). In asenapine-treated patients, the MADRS remission rate was stable regardless of baseline depressive symptom severity (range 64–67%), whereas remission decreased with increasing severity with olanzapine (63–38%) and placebo (49–25%). Reduction in YMRS was significantly greater for asenapine compared with placebo at day 2 across the 3 severity cut-offs and continued to decrease throughout the treatment period. The difference between olanzapine and placebo was statistically significant in mild and moderate patients.

Limitations:
Results are from post-hoc analyses.

Conclusions:
These analyses support the validity of proposed DSM-5 criteria. They confirm that depressive features are frequent in bipolar patients with manic episodes. With increasing baseline severity of depressive features, treatment outcome was poorer with olanzapine and placebo, but remained stable with asenapine.

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