An HMM-based spectrum occupancy predictor for energy efficient cognitive radio

Spectrum sensing is the cornerstone of cognitive radio technology and refers to the process of obtaining awareness of the radio spectrum usage in order to detect the presence of other users. Spectrum sensing algorithms consume considerable energy and time. Prediction methods for inferring the channel occupancy of future time instants have been proposed as a means of improving performance in terms of energy and time consumption. This paper studies the performance of a hidden Markov model (HMM) spectrum occupancy predictor as well as the improvement in sensing energy and time consumption based on real occupancy data obtained in the 2.4GHz ISM band. Experimental results show that the HMM-based occupancy predictor outperforms a kth order Markov and a 1-nearest neighbour (1NN) predictor. Our study also suggests that by employing such a predictive scheme in spectrum sensing, an improvement of up to 66% can be achieved in the required sensing energy and time.

Empirical testing of genuine savings as an indicator of weak sustainability: a three-country analysis of long run trends

Genuine Savings has emerged as a widely-used indicator of sustainable development. In this paper, we use long-term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability. We also show the effects of modelling shocks, such as World War Two and the Great Depression.

Empirical testing of genuine savings as an indicator of weak sustainability: a three-country analysis of long run trends

Genuine Savings has emerged as a widely used indicator of sustainable development. In this paper, we use long -term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of javascript:void(0);a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability.

Modeling energy consumption in error-prone IEEE 802.11-based wireless ad-hoc networks

In the IEEE 802.11 MAC layer protocol, there are different trade-off points between the number of nodes competing for the medium and the network capacity provided to them. There is also a trade-off between the wireless channel condition during the transmission period and the energy consumption of the nodes. Current approaches at modeling energy consumption in 802.11 based networks do not consider the influence of the channel condition on all types of frames (control and data) in the WLAN. Nor do they consider the effect on the different MAC and PHY schemes that can occur in 802.11 networks. In this paper, we investigate energy consumption corresponding to the number of competing nodes in IEEE 802.11's MAC and PHY layers in error-prone wireless channel conditions, and present a new energy consumption model. Analysis of the power consumed by each type of MAC and PHY over different bit error rates shows that the parameters in these layers play a critical role in determining the overall energy consumption of the ad-hoc network. The goal of this research is not only to compare the energy consumption using exact formulae in saturated IEEE 802.11-based DCF networks under varying numbers of competing nodes, but also, as the results show, to demonstrate that channel errors have a significant impact on the energy consumption.

Hospital antibiotic use and its relationship to age-adjusted comorbidity and alcohol-based hand rub consumption

SUMMARY The objective of this study was to evaluate the effect of age-adjusted comorbidity and alcohol-based hand rub on monthly hospital antibiotic usage, retrospectively. A multivariate autoregressive integrated moving average (ARIMA) model was built to relate the monthly use of all antibiotics grouped together with age-adjusted comorbidity and alcohol-based hand rub over a 5-year period (April 2005-March 2010). The results showed that monthly antibiotic use was positively related to the age-adjusted comorbidity index (concomitant effect, coefficient 1·103, P = 0·0002), and negatively related to the use of alcohol-based hand rub (2-month delay, coefficient -0·069, P = 0·0533). Alcohol-based hand rub is considered a modifiable factor and as such can be identified as a target for quality improvement programmes. Time-series analysis may provide a suitable methodology for identifying possible predictive variables that explain antibiotic use in healthcare settings. Future research should examine the relationship between infection control practices and antibiotic use, identify other infection control predictive factors for hospital antibiotic use, and evaluate the impact of enhancing different infection control practices on antibiotic use in a healthcare setting.

Hazardous alcohol consumption is associated with increased levels of B-type natriuretic peptide: evidence from two population-based studies

Russia has very high mortality from cardiovascular disease (CVD), with evidence that heavy drinking may play a role. To throw further light on this association we have studied the association of alcohol with predictors of CVD risk including B-type natriuretic peptide (BNP). Levels of BNP increase primarily in response to abnormal cardiac chamber wall stretch which can occur both as a result of atherosclerosis as well as due to other types of damage to the myocardium. No previous population-based studies have investigated the association with alcohol. We analysed cross-sectional data on drinking behaviour in 993 men aged 25-60 years from the Izhevsk Family Study 2 (IFS2), conducted in the Russian city of Izhevsk in 2008-2009. Relative to non-drinkers, men who drank hazardously had an odds ratio (OR) of being in the top 20 % of the BNP distribution of 4.66 (95 % CI 2.13, 10.19) adjusted for age, obesity, waist-hip ratio, and smoking. Further adjustment for class of hypertension resulted in only slight attenuation of the effect, suggesting that this effect was not secondary to the influence of alcohol on blood pressure. In contrast hazardous drinking was associated with markedly raised ApoA1 and HDL cholesterol levels, but had little impact on levels of ApoB and LDL cholesterol. Similar but less pronounced associations were found in the Belfast (UK) component of the PRIME study conducted in 1991. These findings suggest that the association of heavy drinking with increased risk of cardiovascular disease may be partly due to alcohol-induced non-atherosclerotic damage to the myocardium.

Steady-State and Transient Performance of Biodiesel-Fueled Compression-Ignition-Based Electrical Generation

This paper investigates the performance characteristics of rapeseed methyl ester, EN 14214 biodiesel, when used for electrical generation in compression ignition engines. The work was inspired by the need to replace fossil diesel fuel with a sustainable low carbon alternative while maintaining generator performance, power quality, and compliance with ISO 8528-5. A 50-kVA Perkins diesel engine generator was used to assess the impact of biodiesel with particular regard to gen-set fuel consumption, load acceptance, and associated standards. Tests were performed on the diesel gen-set for islanded and grid-connected modes of operation, hence both steady-state and transient performance were fully explored. Performance comparisons were made with conventional fossil diesel fuel, revealing minimal technical barriers for electrical generation from this sustainable, carbon benign fuel. Recommendations for improved transient performance are proposed and validated through tests.

Oily fish consumption, dietary docosahexaenoic acid and eicosapentaenoic acid intakes, and associations with neovascular age-related macular degeneration

Background: Fish intake, the major source of docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), may reduce the risk of age-related macular degeneration (AMD). Objective: We investigated the association of oily fish and dietary DHA and EPA with neovascular AMD (NV-AMD). Design: Participants aged =65 y in the cross-sectional population-based EUREYE study underwent fundus photography and were interviewed by using a food-frequency questionnaire. Fundus images were graded by the International Classification System for Age Related Maculopathy. Questionnaire data were converted to nutrient intakes with the use of food-composition tables. Survey logistic regression was used to calculate odds ratios (ORs) and 95% CIs of energy-adjusted quartiles of EPA or DHA with NV-AMD, taking into account potential confounders. Results: Dietary intake data and fundus images were available for 105 cases with NV-AMD and for 2170 controls without any features of early or late AMD. Eating oily fish at least once per week compared with less than once per week was associated with a halving of the odds of NV-AMD (OR = 0.47; 95% CI: 0.33, 0.68; P = 0.002). Compared with the lowest quartile, there was a significant trend for decreased odds with increasing quartiles of either DHA or EPA. ORs in the highest quartiles were 0.32 (95% CI: 0.12, 0.87; P = 0.03) for DHA and 0.29 (95% CI: 0.11, 0.73; P = 0.02) for EPA. Conclusions: Eating oily fish at least once per week compared with less than once per week was associated with a halving of the OR for NV-AMD. © 2008 American Society for Nutrition.

Development and validation of a fast monoclonal based disequilibrium enzyme-linked immunosorbent assay for the detection of triphenylmethane dyes and their metabolites in fish

Malachite Green (MG), Crystal Violet (CV) and Brilliant Green (BC) are antibacterial, antifungal and antiparasitic agents that have been used for treatment and prevention of diseases in fish. These dyes are metabolized into reduced leuco forms (LMG, LCV, LBG) that can be present in fish muscles for a long period. Due to the carcinogenic properties they are banned for use in fish for human consumption in many countries including the European Union and the United States. HPLC and LC-MS techniques are generally used for the detection of these compounds and their metabolites in fish. This study presents the development of a fast enzyme-linked immunosorbent assay (ELISA) method as an alternative for screening purposes. A first monoclonal cell line producing antibodies to MG was generated using a hybridoma technique. The antibody had good cross-reactivates with related chromatic forms of triphenylmethane dyes such as CV, BC, Methyl Green, Methyl Violet and Victoria Blue R. The monoclonal antibody (mAb) was used to develop a fast (20 min) disequilibrium ELISA screening method for the detection of triphenylmethanes in fish. By introducing an oxidation step with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) during sample extraction the assay was also used to detect the presence of the reduced metabolites of triphenylmethanes. The detection capability of the assay was 1 ng g(-1) for MG, LMG, CV, LCV and BC which was below the minimum required performance limit (MRPL) for the detection method of total MG (sum of MG and LMG) set by the Commission Decision 2004/25/EC (2 ng g(-1)). The mean recoveries for fish samples spiked at 0.5 MRPL and MRPL levels with MG and LMG were between 74.9 and 117.0% and inter- and intra-assay coefficients of variation between 4.7 and 25.7%. The validated method allows the analysis of a batch of 20 samples in two to three hours. Additionally, this procedure is substantially faster than other ELISA methods developed for MG/LMG thus far. The stable and efficient monoclonal cell line obtained is an unlimited source of sensitive and specific antibody to MG and other triphenylmethanes. (C) 2011 Elsevier B.V. All rights reserved.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.

Inorganic arsenic contents in rice-based infant foods from Spain, UK, China and USA

Spanish gluten-free rice, cereals with gluten, and pureed baby foods were analysed for total (t-As) and inorganic As (i-As) using ICP-MS and HPLC-ICP-MS, respectively. Besides, pure infant rice from China, USA, UK and Spain were also analysed. The i-As contents were significantly higher in gluten-free rice than in cereals mixtures with gluten, placing infants with celiac disease at high risk. All rice-based products displayed a high i-As content, with values being above 60% of the t-As content and the remainder being dimethylarsinic acid (DMA). Approximately 77% of the pure infant rice samples showed contents below 150 µg kg(-1) (Chinese limit). When daily intake of i-As by infants (4-12 months) was estimated and expressed on a bodyweight basis (µg d(-1) kg(-1)), it was higher in all infants aged 8-12 months than drinking water maximum exposures predicted for adults (assuming 1 L consumption per day for a 10 µg L(-1) standard).

The impact of a rice based diet on urinary arsenic

Rice is elevated in arsenic (As) compared to other staple grains. The Bangladeshi community living in the United Kingdom (UK) has a ca. 30-fold higher consumption of rice than white Caucasians. In order to assess the impact of this difference in rice consumption, urinary arsenicals of 49 volunteers in the UK (Bangladeshi n = 37; white Caucasians n = 12) were monitored along with dietary habits. Total urinary arsenic (As(t)) and speciation analysis for dimethylarsinic acid (DMA), monomethylarsonic acid (MA) and inorganic arsenic (iAs) was conducted. Although no significant difference was found for As(t) (median: Bangladeshis 28.4 µg L(-1)) and white Caucasians (20.6 µg L(-1)), the sum of medians of DMA, MA and iAs for the Bangladeshi group was found to be over 3-fold higher (17.9 µg L(-1)) than for the Caucasians (3.50 µg L(-1)). Urinary DMA was significantly higher (p <0.001) in the UK Bangladeshis (median: 16.9 µg DMA L(-1)) than in the white Caucasians (3.16 µg DMA L(-1)) as well as iAs (p <0.001) with a median of 0.630 µg iAs L(-1) for Bangladeshi and 0.250 µg iAs L(-1) for Caucasians. Cationic compounds were significantly lower in the Bangladeshis (2.93 µg L(-1)) than in Caucasians (14.9 µg L(-1)). The higher DMA and iAs levels in the Bangladeshis are mainly the result of higher rice consumption: arsenic is speciated in rice as both iAs and DMA, and iAs can be metabolized, through MA, to DMA by humans. This study shows that a higher dietary intake of DMA alters the DMA/MA ratio in urine. Consequently, DMA/MA ratio as an indication of methylation capacity in populations consuming large quantities of rice should be applied with caution since variation in the quantity and type of rice eaten may alter this ratio.

Association between tortilla consumption and human urinary fumonisin B1 levels in a Mexican population

Fumonisins are mycotoxins produced by Fusarium spp. and commonly contaminate maize and maize products worldwide. Fumonisins are rodent carcinogens and have been associated with human esophageal cancer. However, the lack of a valid exposure biomarker has hindered both the assessment of human exposure and the evaluation of disease risk. A sensitive liquid chromatography-mass spectrometry method to measure urinary fumonisin B1 (FB1) following extraction on Oasis MAX cartridges was established and applied to urine samples from women in a cohort recruited in Morelos County, Mexico. Urinary FB1 was compared with dietary information on tortilla consumption. FB1 recovery in spiked samples averaged 94% as judged by deuterium-labeled FB1 internal standard. Urinary FB1 was determined in 75 samples from women selected based on low, medium, or high consumption of maize-based tortillas. The geometric mean (95% confidence interval) of urinary FB1 was 35.0 (18.8-65.2), 63.1 (36.8-108.2), and 147.4 (87.6-248.0) pg/mL and the frequency of samples above the detection limit (set at 20 pg FB1/mL urine) was 45%, 80%, and 96% for the low, medium, and high groups, respectively. Women with high intake had a 3-fold higher average FB1 levels compared with the "low intake" group (F = 7.3; P = 0.0015). Urinary FB1 was correlated with maize intake (P-trend = 0.001); the correlation remained significant after adjusting for age, education, and place of residence. This study suggests that measurement of urinary FB1 is sufficiently sensitive for fumonisin exposure assessment in human populations and could be a valuable tool in investigating the associated health effects of exposure.

Application-based workload model for wireless sensor node computing platforms

Wireless sensor node platforms are very diversified and very constrained, particularly in power consumption. When choosing or sizing a platform for a given application, it is necessary to be able to evaluate in an early design stage the impact of those choices. Applied to the computing platform implemented on the sensor node, it requires a good understanding of the workload it must perform. Nevertheless, this workload is highly application-dependent. It depends on the data sampling frequency together with application-specific data processing and management. It is thus necessary to have a model that can represent the workload of applications with various needs and characteristics. In this paper, we propose a workload model for wireless sensor node computing platforms. This model is based on a synthetic application that models the different computational tasks that the computing platform will perform to process sensor data. It allows to model the workload of various different applications by tuning data sampling rate and processing. A case study is performed by modeling different applications and by showing how it can be used for workload characterization. © 2011 IEEE.