Detection of dynamic primary user with cooperative spectrum sensing

In this paper we demonstrate that existing cooperative spectrum sensing formulated for static primary users cannot accurately detect dynamic primary users regardless of the information fusion method. Performance error occurs as the sensing parameters calculated by the conventional detector result in sensing performance that violates the sensing requirements. Furthermore, the error is accumulated and compounded by the number of cooperating nodes. To address this limitation, we design and implement the duty cycle detection model for the context of cooperative spectrum sensing to accurately calculate the sensing parameters that satisfy the sensing requirements. We show that longer sensing duration is required to compensate for dynamic primary user traffic.

A comparative investigation of C6-C15 hydrocarbons emitted from a passenger car powered by unleaded petrol and 10% ethanol fuel

Twenty-three non-methane hydrocarbons were captured from the exhaust of a car operating on unleaded petrol (ULP) and 10% ethanol fuels at steady speed on a chassis dynamometer. The compounds were identified and quantified by GC/MS/FID and their emission concentrations at 60 km/h, 80km/h and idle speed were evaluated. The most abundant compounds in the exhaust included n-hexane, n-heptane, benzene, toluene, ethyl benzene, m- and p-xylenes, and methylcyclopentane. Because of the large number of compounds involved, no attempt was made to compare the emission concentrations of the compounds. Rather the sum of the emission concentrations for the suite of compounds identified was compared when the car was powered by ULP and 10% ethanol fuel. It was evident from the results that the emission concentrations and factors were generally higher with ULP than with 10% ethanol fuel. The total emission concentrations with the ULP fuel were 2.8, 4.2 and 2.6 times the corresponding values for the 10% ethanol fuel at 60km/h, 80km/h and idle speed, respectively. The implications of the results on the environment are discussed in the paper.

Genome-wide analysis in a murine Dnmt1 knockdown model identifies epigenetically silenced genes in primary human pituitary tumors

DNA methylation at promoter CpG islands (CGI) is an epigenetic modification associated with inappropriate gene silencing in multiple tumor types. In the absence of a human pituitary tumor cell line, small interfering RNA-mediated knockdown of the maintenance methyltransferase DNA methyltransferase (cytosine 5)-1 (Dnmt1) was used in the murine pituitary adenoma cell line AtT-20. Sustained knockdown induced reexpression of the fully methylated and normally imprinted gene neuronatin (Nnat) in a time-dependent manner. Combined bisulfite restriction analysis (COBRA) revealed that reexpression of Nnat was associated with partial CGI demethylation, which was also observed at the H19 differentially methylated region. Subsequent genome-wide microarray analysis identified 91 genes that were significantly differentially expressed in Dnmt1 knockdown cells (10% false discovery rate). The analysis showed that genes associated with the induction of apoptosis, signal transduction, and developmental processes were significantly overrepresented in this list (P < 0.05). Following validation by reverse transcription-PCR and detection of inappropriate CGI methylation by COBRA, four genes (ICAM1, NNAT, RUNX1, and S100A10) were analyzed in primary human pituitary tumors, each displaying significantly reduced mRNA levels relative to normal pituitary (P < 0.05). For two of these genes, NNAT and S100A10, decreased expression was associated with increased promoter CGI methylation. Induced expression of Nnat in stable transfected AtT-20 cells inhibited cell proliferation. To our knowledge, this is the first report of array-based "epigenetic unmasking" in combination with Dnmt1 knockdown and reveals the potential of this strategy toward identifying genes silenced by epigenetic mechanisms across species boundaries.

Better cars or older cars?: Assessing CO2 emission reduction potential of passenger vehicle replacement programs

The primary motivation for the vehicle replacement schemes that were implemented in many countries was to encourage the purchase of new cars. The basic assumption of these schemes was that these acquisitions would benefit both the economy and the environment as older and less fuel-efficient cars were scrapped and replaced with more fuel-efficient models. In this article, we present a new environmental impact assessment method for assessing the effectiveness of scrappage schemes for reducing CO2 emissions taking into account the rebound effect, driving behavior for older versus new cars and entire lifecycle emissions for during the manufacturing processes of new cars. The assessment of the Japanese scrappage scheme shows that CO2 emissions would only decrease if users of the scheme retained their new gasoline passenger vehicles for at least 4.7 years. When vehicle replacements were restricted to hybrid cars, the reduction in CO2 achieved by the scheme would be 6-8.5 times higher than the emissions resulting from a scheme involving standard, gasoline passenger vehicles. Cost-benefit analysis, based on the emission reduction potential, showed that the scheme was very costly. Sensitivity analysis showed that the Japanese government failed to determine the optimum, or target, car age for scrapping old cars in the scheme. Specifically, scrapping cars aged 13 years and over did not maximize the environmental benefits of the scheme. Consequently, modifying this policy to include a reduction in new car subsidies, focused funding for fuel-efficient cars, and modifying the target car age, would increase environmental benefits. © 2013 Elsevier Ltd.

Price linkages in the copper futures, primary, and scrap markets

This study investigates how markets for different levels of copper purity are interrelated by testing the long-run price linkage and causalities among the copper futures, primary, copper scrap, and brass scrap markets. It is expected that copper markets that deal with high purity levels, such as the futures, primary, and copper scrap markets, have a long-run relationship. However, brass scrap markets where copper with a lower purity is traded may not have a price linkage with other copper markets. The results reveal that a long-run relationship holds between the futures, primary, and copper scrap markets but the brass scrap market does not have a long-run relationship with the other markets. From the short-run and long-run causality tests, we determine that the futures market plays an important role in transmitting price information to other copper markets while such information flow is not found for the brass scrap market.

Conceptions of learning held by Aboriginal students in a tertiary program in Indigenous primary health care

This paper is a description of a pilot investigation into conceptions of learning held by a sample of 10 Aboriginal students in a Bachelors degree courses. Results from this study suggest that this group of students view and approach learning in much the same way as other university students. They mostly hold quantitative conceptions of learning and use repetitive strategies which are potentially at odds with the objectives and procedures of the problems based program in which they are studying.

Vision-based simultaneous localization and mapping in changing outdoor environments

For robots operating in outdoor environments, a number of factors, including weather, time of day, rough terrain, high speeds, and hardware limitations, make performing vision-based simultaneous localization and mapping with current techniques infeasible due to factors such as image blur and/or underexposure, especially on smaller platforms and low-cost hardware. In this paper, we present novel visual place-recognition and odometry techniques that address the challenges posed by low lighting, perceptual change, and low-cost cameras. Our primary contribution is a novel two-step algorithm that combines fast low-resolution whole image matching with a higher-resolution patch-verification step, as well as image saliency methods that simultaneously improve performance and decrease computing time. The algorithms are demonstrated using consumer cameras mounted on a small vehicle in a mixed urban and vegetated environment and a car traversing highway and suburban streets, at different times of day and night and in various weather conditions. The algorithms achieve reliable mapping over the course of a day, both when incrementally incorporating new visual scenes from different times of day into an existing map, and when using a static map comprising visual scenes captured at only one point in time. Using the two-step place-recognition process, we demonstrate for the first time single-image, error-free place recognition at recall rates above 50% across a day-night dataset without prior training or utilization of image sequences. This place-recognition performance enables topologically correct mapping across day-night cycles.

Practical visual odometry for car-like vehicles

A method for calculating visual odometry for ground vehicles with car-like kinematic motion constraints similar to Ackerman's steering model is presented. By taking advantage of this non-holonomic driving constraint we show a simple and practical solution to the odometry calculation by clever placement of a single camera. The method has been implemented successfully on a large industrial forklift and a Toyota Prado SUV. Results from our industrial test site is presented demonstrating the applicability of this method as a replacement for wheel encoder-based odometry for these vehicles.

Integrated chronic disease management in primary-secondary care : a systematic literature review of the evidence

Introduction: Diabetes has traditionally been managed as a single chronic disease state, but it exists with co-morbidities such as depression and metabolic syndrome. Treatment is multifaceted, requiring both primary and secondary care, however, the delivery of diabetes care is often fragmented. Integrated chronic disease management is a growing model of interest, and is underpinned by the chronic care model (CCM), devised as a guide for primary care management of patients with chronic conditions. The model identifies six key elements for effective care, and has shown promise in improving the management of diabetes. Aim: To find empirical evidence of integrated care interventions targeted at co-morbidities including diabetes, across primary/secondary care. Method: A systematic review of peer reviewed literature from PubMed, CINAHL, Embase, Cochrane Library and Joanna Briggs was performed. Studies were reviewed according to inclusion criteria- studies published in English, between 2004-2014, empirical studies, studies with evidence of primary/secondary implementation, and those dealing with chronic co-morbid disease states. Results: 51 studies met the inclusion criteria. Included studies were mostly from the US (38), with five from Australia, UK (2), Canada (2), Netherlands (1), Norway (1), Ireland (1), and one multi-country study. It was found that all interventions adopted at least one (average 3-4) of the chronic care model, with the majority implementing delivery system redesign activities within the primary care practice/s. We found evidence of interventions which significantly reduced emergency department and hospital admissions, improved processes of care, patient health outcomes such as HbA1c, improved patient satisfaction, and reduced costs. Conclusion/Implications for practice: Diabetes exists as a co-morbid disease, requiring both primary and secondary care. We found that integrated care interventions adopting elements of the chronic care model positively impacted on patient outcomes, service utilisation, as well as costs. This review has highlighted that it may not be necessary to adopt all CCM elements to improve clinical outcomes, patient satisfaction and costs.

Q-RARA : a rapid and rigorous method for researching small, primary health care organisations

Understanding the organisational processes driving quality primary care is crucial to the maintaining and improving practice. Qualitative methods are increasingly popular in health services research, but this area is dominated by interview studies. Multiple qualitative methods are rarely used in a systematically integrated fashion. We developed a method to study small primary health care organizations using rapid appraisal and qualitative mixed methods: Q-RARA – Qualitative Rapid Appraisal, Rigorous Analysis