Optimal energy efficiency link adaptation in IEEE 802.15.6 IR-UWB body area networks

© 2014 IEEE. We propose a novel link adaptation mechanism to maximize energy efficiency in IEEE 802.15.6 impulse radio ultra wideband (IR-UWB) wireless body area networks (WBANs). We consider noncoherent energy detection and autocorrelation receivers, suitable for low complexity implementations. The amount of captured energy is first modeled for the on-body WBAN channel. Using our energy capture model and Gaussian approximations for the decision statistic, the error performance of various physical layer modes of the IEEE 802.15.6 standard is derived assuming intra-symbol interference. We refer to the IEEE 802.15.6 specification as a use case. The proposed adaptation scheme can be applied to any other IR-UWB system with noncoherent receivers and is based on the estimated signal to noise ratio and the channel's energy capture index for which we propose unbiased estimators

Energy-delay tradeoffs in impulse-based ultra-wideband body area networks with noncoherent receivers

© 2014 IEEE. In this paper we address the problem of rate scheduling in the Impulse Radio (IR) ultra-wideband (UWB) wireless body area networks (WBANs) and the minimum energy required to stabilize the queuing system. Targeting low complexity WBAN applications, we assume noncoherent receivers based on energy detection and autocorrelation for all nodes. The coordinating node can minimize the average energy consumption of the system and achieve the queue backlog stability of the sensor nodes by controlling the number of pulses per symbol. We first illustrate the necessary and sufficient conditions of network stability for a multi-mode UWB system and then propose a feasible rate scheduling algorithm based on the Lyapunov optimization theory. The scheduling algorithm uses the instantaneous channel state information and the length of the local queue of all sensor nodes and can approach the optimal energy-delay tradeoff of the network. We apply our theoretical framework to the IR-UWB physical layer of the IEEE 802.15.6 standard and extract the optimal physical layer modes that can achieve the desired energy-delay tradeoff

Just Culture – A Case of Mistaken Identity

https://openworks.mdanderson.org/edwk22/1006/thumbnail.jp

Optimizing Taq Polymerase Concentration for Improved Signal-to-Noise in the Broad Range Detection of Low Abundance Bacteria

BACKGROUND:PCR in principle can detect a single target molecule in a reaction mixture. Contaminating bacterial DNA in reagents creates a practical limit on the use of PCR to detect dilute bacterial DNA in environmental or public health samples. The most pernicious source of contamination is microbial DNA in DNA polymerase preparations. Importantly, all commercial Taq polymerase preparations inevitably contain contaminating microbial DNA. Removal of DNA from an enzyme preparation is problematical. METHODOLOGY/PRINCIPAL FINDINGS:This report demonstrates that the background of contaminating DNA detected by quantitative PCR with broad host range primers can be decreased greater than 10-fold through the simple expedient of Taq enzyme dilution, without altering detection of target microbes in samples. The general method is: For any thermostable polymerase used for high-sensitivity detection, do a dilution series of the polymerase crossed with a dilution series of DNA or bacteria that work well with the test primers. For further work use the concentration of polymerase that gave the least signal in its negative control (H(2)O) while also not changing the threshold cycle for dilutions of spiked DNA or bacteria compared to higher concentrations of Taq polymerase. CONCLUSIONS/SIGNIFICANCE:It is clear from the studies shown in this report that a straightforward procedure of optimizing the Taq polymerase concentration achieved "treatment-free" attenuation of interference by contaminating bacterial DNA in Taq polymerase preparations. This procedure should facilitate detection and quantification with broad host range primers of a small number of bona fide bacteria (as few as one) in a sample

Inference of financial networks using the normalised mutual information rate

In this paper we study data from financial markets using an information theory tool that we call the normalised Mutual Information Rate and show how to use it to infer the underlying network structure of interrelations in foreign currency exchange rates and stock indices of 14 countries world-wide and the European Union. We first present the mathematical method and discuss about its computational aspects, and then apply it to artificial data from chaotic dynamics and to correlated random variates. Next, we apply the method to infer the network structure of the financial data. Particularly, we study and reveal the interrelations among the various foreign currency exchange rates and stock indices in two separate networks for which we also perform an analysis to identify their structural properties. Our results show that both are small-world networks sharing similar properties but also having distinct differences in terms of assortativity. Finally, the consistent relationships depicted among the 15 economies are further supported by a discussion from the economics view point

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Analysing the Impact of Machine Learning to Model Subjective Mental Workload: A Case Study in Third-Level Education

Mental workload measurement is a complex multidisciplinary research area that includes both the theoretical and practical development of models. These models are aimed at aggregating those factors, believed to shape mental workload, and their interaction, for the purpose of human performance prediction. In the literature, models are mainly theory-driven: their distinct development has been influenced by the beliefs and intuitions of individual scholars in the disciplines of Psychology and Human Factors. This work presents a novel research that aims at reversing this tendency. Specifically, it employs a selection of learning techniques, borrowed from machine learning, to induce models of mental workload from data, with no theoretical assumption or hypothesis. These models are subsequently compared against two well-known subjective measures of mental workload, namely the NASA Task Load Index and the Workload Profile. Findings show how these data-driven models are convergently valid and can explain overall perception of mental workload with a lower error

Ankle proprioception is not targeted by exercises on an unstable surface

Item does not contain fulltextLaboratory study using a repeated measures design. The aim of this study was to determine if ankle proprioception is targeted in exercises on unstable surfaces. Lateral ankle sprain (LAS) has recurrence rates over 70%, which are believed to be due to a reduced accuracy of proprioceptive signals from the ankle. Proprioceptive exercises in rehabilitation of LAS mostly consist of balancing activities on an unstable surface. The methods include 100 healthy adults stood barefoot on a solid surface and a foam pad over a force plate, with occluded vision. Mechanical vibration was used to stimulate proprioceptive output of muscle spindles of triceps surae and lumbar paraspinal musculature. Each trial lasted for 60 s; vibration was applied from the 15th till the 30th second. Changes in mean velocity and mean position of the center of pressure (CoP) as a result of muscle vibration were calculated. Results show that on foam, the effect of triceps surae vibration on mean CoP velocity was significantly smaller than on a solid surface, while for paraspinal musculature vibration the effect was bigger on foam than on solid surface. Similar effects were seen for mean CoP displacement as outcome. Exercises on unstable surfaces appear not to target peripheral ankle proprioception. Exercises on an unstable surface may challenge the capacity of the central nervous system to shift the weighting of sources of proprioceptive signals on balance

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO