Improving the tolerance of stochastic LDPC decoders to overclocking-induced timing errors: a tutorial and design example

Channel codes such as Low-Density Parity-Check (LDPC) codes may be employed in wireless communication schemes for correcting transmission errors. This tolerance to channel-induced transmission errors allows the communication schemes to achieve higher transmission throughputs, at the cost of requiring additional processing for performing LDPC decoding. However, this LDPC decoding operation is associated with a potentially inadequate processing throughput, which may constrain the attainable transmission throughput. In order to increase the processing throughput, the clock period may be reduced, albeit this is at the cost of potentially introducing timing errors. Previous research efforts have considered a paucity of solutions for mitigating the occurrence of timing errors in channel decoders, by employing additional circuitry for detecting and correcting these overclocking-induced timing errors. Against this background, in this paper we demonstrate that stochastic LDPC decoders (LDPC-SDs) are capable of exploiting their inherent error correction capability for correcting not only transmission errors, but also timing errors, even without the requirement for additional circuitry. Motivated by this, we provide the first comprehensive tutorial on LDPC-SDs. We also propose a novel design flow for timing-error-tolerant LDPC decoders. We use this to develop a timing error model for LDPC-SDs and investigate how their overall error correction performance is affected by overclocking. Drawing upon our findings, we propose a modified LDPC-SD, having an improved timing error tolerance. In a particular practical scenario, this modification eliminates the approximately 1 dB performance degradation that is suffered by an overclocked LDPC-SD without our modification, enabling the processing throughput to be increased by up to 69.4%, which is achieved without compromising the error correction capability or processing energy consumption of the LDPC-SD

Electron impact ionization loading of a surface electrode ion trap

We demonstrate a method for loading surface electrode ion traps by electron impact ionization. The method relies on the property of surface electrode geometries that the trap depth can be increased at the cost of more micromotion. By introducing a buffer gas, we can counteract the rf heating assocated with the micromotion and benefit from the larger trap depth. After an initial loading of the trap, standard compensation techniques can be used to cancel the stray fields resulting from charged dielectric and allow for the loading of the trap at ultra-high vacuum.Comment: 4 pages, 5 eps figures. Shift in focus, minor correction

Is more data always better? A simulation study of benefits and limitations of integrated distribution models

Species distribution models are popular and widely applied ecological tools. Recent increases in data availability have led to opportunities and challenges for species distribution modelling. Each data source has different qualities, determined by how it was collected. As several data sources can inform on a single species, ecologists have often analysed just one of the data sources, but this loses information, as some data sources are discarded. Integrated distribution models (IDMs) were developed to enable inclusion of multiple datasets in a single model, whilst accounting for different data collection protocols. This is advantageous because it allows efficient use of all data available, can improve estimation and account for biases in data collection. What is not yet known is when integrating different data sources does not bring advantages. Here, for the first time, we explore the potential limits of IDMs using a simulation study integrating a spatially biased, opportunistic, presence‐only dataset with a structured, presence–absence dataset. We explore four scenarios based on real ecological problems; small sample sizes, low levels of detection probability, correlations between covariates and a lack of knowledge of the drivers of bias in data collection. For each scenario we ask; do we see improvements in parameter estimation or the accuracy of spatial pattern prediction in the IDM versus modelling either data source alone? We found integration alone was unable to correct for spatial bias in presence‐only data. Including a covariate to explain bias or adding a flexible spatial term improved IDM performance beyond single dataset models, with the models including a flexible spatial term producing the most accurate and robust estimates. Increasing the sample size of presence–absence data and having no correlated covariates also improved estimation. These results demonstrate under which conditions integrated models provide benefits over modelling single data sources

Signed zeros of Gaussian vector fields-density, correlation functions and curvature

We calculate correlation functions of the (signed) density of zeros of Gaussian distributed vector fields. We are able to express correlation functions of arbitrary order through the curvature tensor of a certain abstract Riemann-Cartan or Riemannian manifold. As an application, we discuss one- and two-point functions. The zeros of a two-dimensional Gaussian vector field model the distribution of topological defects in the high-temperature phase of two-dimensional systems with orientational degrees of freedom, such as superfluid films, thin superconductors and liquid crystals.Comment: 14 pages, 1 figure, uses iopart.cls, improved presentation, to appear in J. Phys.

Trace Gas and Particle Emissions from Fires in Large Diameter and Belowground Biomass Fuels

[1] We adopt a working definition of residual smoldering combustion (RSC) as biomass combustion that produces emissions that are not lofted by strong fire-induced convection. RSC emissions can be produced for up to several weeks after the passage of a flame front and they are mostly unaffected by flames. Fuels prone to RSC include downed logs, duff, and organic soils. Limited observations in the tropics and the boreal forest suggest that RSC is a globally significant source of emissions to the troposphere. This source was previously uncharacterized. We measured the first emission factors (EF) for RSC in a series of laboratory fires and in a wooded savanna in Zambia, Africa. We report EFRSC for both particles with diameter \u3c2.5 μm (PM2.5) and the major trace gases as measured by open-path Fourier transform infrared (OP-FTIR) spectroscopy. The major trace gases include carbon dioxide, carbon monoxide, methane, ethane, ethene, acetylene, propene, formaldehyde, methanol, acetic acid, formic acid, glycolaldehyde, phenol, furan, ammonia, and hydrogen cyanide. We show that a model used to predict trace gas EF for fires in a wide variety of aboveground fine fuels fails to predict EF for RSC. For many compounds, our EF for RSC-prone fuels from the boreal forest and wooded savanna are very different from the EF for the same compounds measured in fire convection columns above these ecosystems. We couple our newly measured EFRSC with estimates of fuel consumption by RSC to refine emission estimates for fires in the boreal forest and wooded savanna. We find some large changes in estimates of biomass fire emissions with the inclusion of RSC. For instance, the wooded savanna methane EF increases by a factor of 2.5 even when RSC accounts for only 10% of fuel consumption. This shows that many more measurements of fuel consumption and EF for RSC are needed to improve estimates of biomass burning emissions

Effect of provision of an integrated neonatal survival kit and early cognitive stimulation package by community health workers on developmental outcomes of infants in Kwale County, Kenya: study protocol for a cluster randomized trial

Background: Each year, more than 200 million children under the age of 5 years, almost all in low- and middle-income countries (LMICs), fail to achieve their developmental potential. Risk factors for compromised development often coexist and include inadequate cognitive stimulation, poverty, nutritional deficiencies, infection and complications of being born low birthweight and/or premature. Moreover, many of these risk factors are closely associated with newborn morbidity and mortality. As compromised development has significant implications on human capital, inexpensive and scalable interventions are urgently needed to promote neurodevelopment and reduce risk factors for impaired development. Method/Design: This cluster randomized trial aims at evaluating the impact of volunteer community health workers delivering either an integrated neonatal survival kit, an early stimulation package, or a combination of both interventions, to pregnant women during their third trimester of pregnancy, compared to the current standard of care in Kwale County, Kenya. The neonatal survival kit comprises a clean delivery kit (sterile blade, cord clamp, clean plastic sheet, surgical gloves and hand soap), sunflower oil emollient, chlorhexidine, ThermoSpotTM, Mylar infant sleeve, and a reusable instant heater. Community health workers are also equipped with a portable hand-held electric scale. The early cognitive stimulation package focuses on enhancing caregiver practices by teaching caregivers three key messages that comprise combining a gentle touch with making eye contact and talking to children, responsive feeding and caregiving, and singing. The primary outcome measure is child development at 12 months of age assessed with the Protocol for Child Monitoring (Infant and Toddler version). The main secondary outcome is newborn mortality. Discussion: This study will provide evidence on effectiveness of delivering an innovative neonatal survival kit and/or early stimulation package to pregnant women in Kwale County, Kenya. Study findings will help inform policy on the most appropriate interventions for promoting healthy brain development and reduction of newborn morbidity and mortality in Kenya and other similar settings. Trial registration: ClinicalTrial.gov NCT02208960 (August 1, 2014

Evidence of inverted-gravity driven variation in predictive sensorimotor function.

We move our eyes to place the fovea into the part of a viewed scene currently of interest. Recent evidence suggests that each human has signature patterns of eye movements like handwriting which depend on their sensitivity, allocation of attention and experience. Use of implicit knowledge of how earth's gravity influences object motion has been shown to aid dynamic perception. We used a projected ball tracking task with a plain background offering no context cues to probe the effect of acquired experience about physical laws of gravitation on performance differences of 44 participants under a simulated gravity and an atypical (upward) antigravity condition. Performance measured by the unsigned difference between instantaneous eye and stimulus positions (RMSE) was consistently worse in the antigravity condition. In the vertical RMSE, participants took about 200ms longer to improve to the best performance for antigravity compared to gravity trials. The antigravity condition produced a divergence of individual performance which was correlated with levels of questionnaire based quantified traits of schizotypy but not control traits. Grouping participants by high or low traits revealed a negative relationship between schizotypy traits level and both initiation and maintenance of tracking, a result consistent with trait related impoverished sensory prediction. The findings confirm for the first time that where cues enabling exact estimation of acceleration are unavailable, knowledge of gravity contributes to dynamic prediction improving motion processing. With acceleration expectations violated, we demonstrate that antigravity tracking could act as a multivariate diagnostic window into predictive brain function

How do leaf and ecosystem measures of water-use efficiency compare?

The terrestrial carbon and water cycles are intimately linked: the carbon cycle is driven by photosynthesis, while the water balance is dominated by transpiration, and both fluxes are controlled by plant stomatal conductance. The ratio between these fluxes, the plant wateruse efficiency (WUE), is a useful indicator of vegetation function. WUE can be estimated using several techniques, including leaf gas exchange, stable isotope discrimination, and eddy covariance. Here we compare global compilations of data for each of these three techniques. We show that patterns of variation in WUE across plant functional types (PFTs) are not consistent among the three datasets. Key discrepancies include the following: leaf-scale data indicate differences between needleleaf and broadleaf forests, but ecosystem-scale data do not; leaf-scale data indicate differences between C3 and C4 species, whereas at ecosystem scale there is a difference between C3 and C4 crops but not grasslands; and isotope-based estimates of WUE are higher than estimates based on gas exchange for most PFTs. Our study quantifies the uncertainty associated with different methods of measuring WUE, indicates potential for bias when using WUE measures to parameterize or validate models, and indicates key research directions needed to reconcile alternative measures of WUE

Development of a Certificate in Healthcare Improvement for Inter-Professional Teams

Introduction To address gaps in care team improvement-science education and connect geographically dispersed learners, we created a healthcare improvement certificate program, now completing the third program year, for inter-professional (IP) healthcare teams, including third year medical students. Methods This hybrid learning program consists of five modules: Learning Healthcare Systems, Improvement Science, Patient Safety and Diagnostic Error, Population Health and Health Equity and Leading Change. The curricular materials are comprised of focused readings, concise videos, faculty-moderated discussion boards, weekly synchronous calls of participants with faculty, and a longitudinal improvement project. The faculty are content experts, and worked with a curricular designer to define learning objectives and develop content. Results We have completed three years of this six-month program, training 61 participants (17 of whom were medical students) at 14 sites. In the third year, several medical students participated without an IP team. Development of the materials has been iterative, with feedback from learners and faculty used to shape the materials. Discussion We demonstrate the development and rollout of a hybrid-learning program for diverse and geographically dispersed IP teams, including medical students. Time restrictions limited the depth of topics, and scheduling overlap caused some participants to miss the interactive calls. We plan to evaluate the utility of the program for participants over time, using qualitative methods. Conclusion This educational model is feasible for IP teams studying improvement science and implementing change projects, and can be adopted to dispersed geographic settings

Futureproofing [18F]Fludeoxyglucose manufacture at an Academic Medical Center

Abstract Background We recently upgraded our [18F]fludeoxyglucose (FDG) production capabilities with the goal of futureproofing our FDG clinical supply, expanding the number of batches of FDG we can manufacture each day, and improving patient throughput in our nuclear medicine clinic. In this paper we report upgrade of the synthesis modules to the GE FASTLab 2 platform (Phase 1) and cyclotron updates (Phase 2) from both practical and regulatory perspectives. We summarize our experience manufacturing FDG on the FASTLab 2 module with a high-yielding self-shielded niobium (Nb) fluorine-18 target. Results Following installation of Nb targets for production of fluorine-18, a 55 μA beam for 22 min generated 1330 ± 153 mCi of [18F]fluoride. Using these cyclotron beam parameters in combination with the FASTLab 2, activity yields (AY) of FDG were 957 ± 102 mCi at EOS, corresponding to 72% non-corrected AY (n = 235). Our workflow, inventory management and regulatory compliance have been greatly simplified following the synthesis module and cyclotron upgrades, and patient wait times for FDG PET have been cut in half at our nuclear medicine clinic. Conclusions The combination of FASTlab 2 and self-shielded Nb fluorine-18 targets have improved our yield of FDG, and enabled reliable and repeatable manufacture of the radiotracer for clinical use.https://deepblue.lib.umich.edu/bitstream/2027.42/145727/1/41181_2018_Article_48.pd