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The provinces of Alberta and Saskatchewan account for 70% of Canada's methane emissions from the oil and gas sector. In 2018, the Government of Canada introduced methane regulations to reduce emissions from the sector by 40-45% from the 2012 levels by 2025. Complementary to inventory accounting methods, the effectiveness of regulatory practices to reduce emissions can be assessed using atmospheric measurements and inverse models. Total anthropogenic (oil and gas, agriculture, and waste) emission rates of methane from 2010 to 2017 in Alberta and Saskatchewan were derived using hourly atmospheric methane measurements over a six-month winter period from October to March. Scaling up the winter estimate to annual indicated an anthropogenic emission rate of 3.7 ± 0.7 MtCH4/year, about 60% greater than that reported in Canada's National Inventory Report (2.3 MtCH4). This discrepancy is tied primarily to the oil and gas sector emissions as the reported emissions from livestock operations (0.6 MtCH4) are well substantiated in both top-down and bottom-up estimates and waste management (0.1 MtCH4) emissions are small. The resulting estimate of 3.0 MtCH4 from the oil and gas sector is nearly twice that reported in Canada's National Inventory (1.6 MtCH4).

Introduction. Rapid and reliable detection of carbapenemase-producing Enterobacterales (CPE) from surveillance cultures is critical in supporting a good infection control programme. We implemented a new algorithm for CPE detection incorporating the NG Test CARBA 5 in January 2019. Aim. Our goals were to compare turnaround time (TAT), costs and staff requirements between the old and new algorithm, and to evaluate the performance of the CARBA 5 test directly on colonies grown on CARBA Smart agar. Methodology. We analysed and compared the TAT of CPE surveillance cultures processed using the old and new CPE screening algorithm. The total actual reagent costs and staff requirements for the new CPE algorithm were compared with the estimated costs and staff requirements of the old CPE algorithm. Results. Of 197 isolates included in the evaluation of the new algorithm, 64 were positive for carbapenemases by both CARBA 5 and Xpert Carba-R assay. Of the 133 that were negative, two were found to harbour NDM and IMI genotypes. Significant improvements in TAT were achieved with 88.7 % of cultures with CPE, reported on the same day as growth was observed on CARBA Smart agar compared to none in the old algorithm. The new algorithm incurred lower costs and, based on our workload, the new algorithm is estimated to save 28.9 man-hours annually. Conclusion. CARBA 5 performs well on colonies growing on CARBA Smart agar and significant improvements in TAT can be achieved without incurring additional costs or staff requirements.

Accessible and adaptable nucleic acid diagnostics remains a critical challenge in managing the evolving COVID‐19 pandemic. Here, an integrated molecular nanotechnology that enables direct and programmable detection of SARS‐CoV‐2 RNA targets in native patient specimens is reported. Termed synergistic coupling of responsive equilibrium in enzymatic network (SCREEN), the technology leverages tunable, catalytic molecular nanostructures to establish an interconnected, collaborative architecture. SCREEN mimics the extraordinary organization and functionality of cellular signaling cascades. Through programmable enzyme–DNA nanostructures, SCREEN activates upon interaction with different RNA targets to initiate multi‐enzyme catalysis; through system‐wide favorable equilibrium shifting, SCREEN directly transduces a single target binding into an amplified electrical signal. To establish collaborative equilibrium coupling in the architecture, a computational model that simulates all reactions to predict overall performance and optimize assay configuration is developed. The developed platform achieves direct and sensitive RNA detection (approaching single‐copy detection), fast response (assay reaction is completed within 30 min at room temperature), and robust programmability (across different genetic loci of SARS‐CoV‐2). When clinically evaluated, the technology demonstrates robust and direct detection in clinical swab lysates to accurately diagnose COVID‐19 patients., A molecular nanotechnology is developed utilizing interconnected enzyme–DNA nanostructures to achieve cooperative multi‐enzyme catalysis. Through programmable nanostructures and favorable equilibrium coupling in the system architecture, the technology achieves sensitive and versatile detection for the direct measurement of SARS‐CoV‐2 RNA targets in native patient specimens (30 min at room temperature).

Carbapenemase-producing Enterobacterales (CPE) infection control practices are based on the paradigm that detected carriers in the hospital transmit to other patients who stay in the same ward. The role of plasmid-mediated transmission at population level remains largely unknown. In this retrospective cohort study over 4.7 years involving all multi-disciplinary public hospitals in Singapore, we analysed 779 patients who acquired CPE (1215 CPE isolates) detected by clinical or surveillance cultures. 42.0% met putative clonal transmission criteria, 44.8% met putative plasmid-mediated transmission criteria and 13.2% were unlinked. Only putative clonal transmissions associated with direct ward contact decreased in the second half of the study. Both putative clonal and plasmid-mediated transmission associated with indirect (no temporal overlap in patients’ admission period) ward and hospital contact did not decrease during the study period. Indirect ward and hospital contact were identified as independent risk factors associated with clonal transmission. In conclusion, undetected CPE reservoirs continue to evade hospital infection prevention measures. New measures are needed to address plasmid-mediated transmission, which accounted for 50% of CPE dissemination.

Transition-state molecular switches enable hyper responsive detection of SARS-CoV-2 in native clinical samples., Despite the importance of nucleic acid testing in managing the COVID-19 pandemic, current detection approaches remain limited due to their high complexity and extensive processing. Here, we describe a molecular nanotechnology that enables direct and sensitive detection of viral RNA targets in native clinical samples. The technology, termed catalytic amplification by transition-state molecular switch (CATCH), leverages DNA-enzyme hybrid complexes to form a molecular switch. By ratiometric tuning of its constituents, the multicomponent molecular switch is prepared in a hyperresponsive state—the transition state—that can be readily activated upon the binding of sparse RNA targets to turn on substantial enzymatic activity. CATCH thus achieves superior performance (~8 RNA copies/μl), direct fluorescence detection that bypasses all steps of PCR (

COVID‐19 is the latest global pandemic caused by severe acute respiratory syndrome coronavirus ‐2 (SARS‐CoV‐2). There have been seven pathogenic Human Coronaviruses (HCoVs) which cause respiratory infections. Common cold coronaviruses HCoV‐229E, HCoV‐OC43, HCoV‐NL63, HCoV‐HKU1 are the four endemic HCoVs. SARS‐CoV‐1, MERS‐CoV, SARS‐CoV‐2 are zoonotic emerging epidemic pathogens with significant morbidity, mortality and economic impact. The endemic HCoVs have been known to cause co‐infections or can be co‐detected with each other or with other respiratory viruses. In general, respiratory viral co‐infections are recognized more commonly today with the use of respiratory multiplex molecular diagnostic panels. Clinicians need to be aware of co‐infections among HCoVs. A high degree of suspicion in this rapidly evolving outbreak is required in order to make the diagnosis. This is vital if we are to try and contain and control the spread of the COVID‐19. This article is protected by copyright. All rights reserved.

In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high-spatiotemporal-resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km×10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower-resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate the high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations based on comparisons to surface and aircraft observations. In addition, the bias and standard deviation of forecast error in boreal summer are reduced by the regional model. Better representation of model topography in the regional model results in improved simulation of the CO2 diurnal cycle compared to the global model at Walnut Grove, California. The new regional model will form the basis of a flux inversion system that estimates regional-scale fluxes of GHGs over Canada.

Programmable Detection of SARS‐CoV‐2 In article number 2101155, Huilin Shao and co‐workers report the collaborative coupling of enzyme–DNA nanostructures to establish multi‐enzyme catalysis. Through programmable nanostructures and favorable equilibrium architecture, the technology achieves direct and sensitive detection of SARS‐CoV‐2 RNA in native patient samples, within 30 minutes at room temperature. [Image: see text]

Objectives To determine if using alternative streaking patterns on the BD Kiestra InoqulA can impact colony isolation and improve turnaround time (TAT) of methicillin-resistant Staphylococcus aureus (MRSA) and carbapenem-resistant Enterobacterales (CRE) screening samples. Methods A total of 1571 positive MRSA screening samples were studied, of which 755 screening plates were streaked by the standard pattern (4-Quadrant uniform S200) and 816 plates were streaked by an alternative pattern (Zigzag 3.5–1 S200). A total of 424 CRE-positive screening samples were studied, of which 211 screening plates were streaked by the standard pattern (Zigzag 2.5–1 inoc S200) and 213 plates were streaked by an alternative customized pattern (Zigzag 3.5–1 vertstreak s200). Results There was a reduction in the number of MRSA screening plates with insufficient isolated colonies for confirmatory testing from 75 plates (9.9%) when using the standard pattern to 18 plates (2.2%) when using the alternative streaking pattern. MRSA cases with a TAT above 36 hours also reduced significantly from 144 (19.1%) to 20 (2.4%). The number of CRE screening plates with insufficient colonies for same-day confirmatory testing reduced from 16 (7.6%) when using the standard pattern to two plates (1.1%) when using the alternative customized pattern. CRE cases with a TAT above 36 hours also reduced from 16 (7.6%) to seven (3.3%). Conclusions The change in streaking patterns resulted in more plates with sufficient isolated colonies as well as reduced man-hours and materials required to perform subculture of mixed colonies and overall improvements in TAT.

In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high spatio-temporal resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km × 10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations, based on comparisons to surface and aircraft observations. In addition, reduced bias and standard deviation of forecast error in boreal summer are obtained by the regional model. Better representation of model topography in the regional model reduces transport and representation errors significantly compared to the global model, especially in regions of complex topography, as revealed by the more precise and detailed structure of the CO2 diurnal cycle produced at observation sites and in model space. The new regional model will form the basis of a flux inversion system that estimates regional scale fluxes of GHGs over Canada.

Answer: Prosthetic knee septic arthritis due to Histoplasma capsulatum. The tuberculate macroconidia with thick-walled, radial, and finger-like projections are suggestive of Histoplasma capsulatum. Dimorphism was demonstrated at 37°C (yeast-like colonies) and at 30°C (floccose mold-like colonies

A 68-year-old Chinese male presented with right knee pain and swelling 9 months after an elective right total knee replacement (TKR) for osteoarthritis. He had a past medical history of end-stage renal failure requiring hemodialysis. Physical examination revealed mild effusion and increased warmth

Carbapenem-resistant Enterobacteriaceae (CRE) can be mechanistically classified into carbapenemase-producing Enterobacteriaceae (CPE) and non-carbapenemase-producing carbapenem nonsusceptible Enterobacteriaceae (NCPCRE). We sought to investigate the effect of antecedent carbapenem exposure as a risk factor for NCPCRE versus CPE. Among all patients with CRE colonization and infection, we conducted a case-control study comparing patients with NCPCRE (cases) and patients with CPE (controls). The presence of carbapenemases was investigated with phenotypic tests followed by PCR for predominant carbapenemase genes. We included 843 unique patients with first-episode CRE, including 387 (45.9%) NCPCRE and 456 (54.1%) CPE. The resistance genes detected in CPEs were blaNDM (42.8%), blaKPC (38.4%), and blaOXA-48-like (12.1%). After adjusting for confounders and clustering at the institutional level, the odds of prior 30-day carbapenem exposure was three times higher among NCPCRE than CPE patients (adjusted odds ratio [aOR], 3.48; 95% confidence interval [CI], 2.39 to 5.09; P

A new model for greenhouse gas transport has been developed based on Environment and Climate Change Canada's operational weather and environmental prediction models. When provided with realistic posterior fluxes for CO2, the CO2 simulations compare well to NOAA's CarbonTracker fields and to near-surface continuous measurements, columns from the Total Carbon Column Observing Network (TCCON) and NOAA aircraft profiles. This coupled meteorological and tracer transport model is used to study the predictability of CO2. Predictability concerns the quantification of model forecast errors and thus of transport model errors. CO2 predictions are used to compute model–data mismatches when solving flux inversion problems and the quality of such predictions is a major concern. Here, the loss of meteorological predictability due to uncertain meteorological initial conditions is shown to impact CO2 predictability. The predictability of CO2 is shorter than that of the temperature field and increases near the surface and in the lower stratosphere. When broken down into spatial scales, CO2 predictability at the very largest scales is mainly due to surface fluxes but there is also some sensitivity to the land and ocean surface forcing of meteorological fields. The predictability due to the land and ocean surface is most evident in boreal summer when biospheric uptake produces large spatial gradients in the CO2 field. This is a newly identified source of uncertainty in CO2 predictions but it is expected to be much less significant than uncertainties in fluxes. However, it serves as an upper limit for the more important source of transport error and loss of predictability, which is due to uncertain meteorological analyses. By isolating this component of transport error, it is demonstrated that CO2 can only be defined on large spatial scales due to the presence of meteorological uncertainty. Thus, for a given model, there is a spatial scale below which fluxes cannot be inferred simply due to the fact that meteorological analyses are imperfect. These unresolved spatial scales correspond to small scales near the surface but increase with altitude. By isolating other components of transport error, the largest or limiting error can be identified. For example, a model error due to the lack of convective tracer transport was found to impact transport error on the very largest (wavenumbers less than 5) spatial scales. Thus for wavenumbers greater than 5, transport model error due to meteorological analysis uncertainty is more important for our model than the lack of convective tracer transport.

© 1997-2012 IEEE. The Internet of Things (IoT) represents a new class of applications that can benefit from cloud infrastructure. However, directly connecting smart devices to the cloud has multiple disadvantages and is unlikely to keep up with the growing speed of the IoT or the diverse needs of IoT applications. Here, the authors argue that fundamental IoT properties prevent the current approach from scaling. What's missing is a well-architected system extending cloud functionality and providing seamless interplay among heterogeneous components closer to the edge in the IoT space. Raising the level of abstraction to a data-centric design-focused around the distribution, preservation, and protection of information-better matches the IoT. To address such problems with the cloud-centric architecture, the authors present their early work on a distributed platform, the Global Data Plane.

The rapid and accurate detection of carbapenemase-producing Enterobacteriaceae (CPE) is necessary for patient management and infection control measures. We compared the performance of the BD Phoenix CPO Detect with that of a homemade Carba NP assay and a modified carbapenem inactivation method (mCIM) by challenging all 3 assays with 190 isolates of Enterobacteriaceae with meropenem MICs of >0.125 mg/liter. A total of 160 isolates produced KPC-, IMI-1-, NDM-, IMP-, and OXA-type carbapenemases, while 30 isolates were negative for carbapenemase production. The sensitivity and specificity were 90.6% (95% confidence interval [CI], 85.0% to 94.7%) and 100.0% (95% CI, 88.4% to 100.0%), respectively, for the Carba NP; 100.0% (95% CI, 97.7% to 100.0%) and 96.7% (95% CI, 82.7% to 99.9%), respectively, for the mCIM; and 89.4% (95% CI, 83.5% to 93.7%) and 66.7% (95% CI, 47.2% to 82.7%), respectively, for the BD Phoenix CPO Detect. In particular, the BD CPO Detect failed to detect a significant number of CPE with IMI-1. While the BD Phoenix CPO Detect is able to classify carbapenemases and is built into routine susceptibility testing with the potential to reduce the time to CPE detection, its low specificity means that a positive result will need confirmatory testing by another method.

A regional greenhouse gas flux inversion system (REFIST v1.0) is described. This paper provides a comprehensive evaluation of REFIST for three provinces in Canada that include Alberta (AB), Saskatchewan (SK) and Ontario (ON). Using year 2009 fossil fuel CO2 CarbonTracker model results as the target, the synthetic data experiment analyses examined the impacts of the errors from the Bayesian optimisation method, inversion time span, prior flux distribution, region definition and the atmospheric transport model, as well as their interactions. The posterior fluxes were estimated by two different optimisation methods, the Markov chain Monte Carlo (MCMC) simulation and cost function minimization (CFM) methods. Increasing the number of sub-regions (unknowns) beyond "optimality" can produce unstable and unrealistic fluxes for some sub-regions, and does not yield significantly different flux estimates overall. The two optimisation methods can provide comparable, stable and realistic flux results when the transport model error is small (prior R2~0.8 with synthetic observations), but both methods present difficulty when the transport model error is large (prior R2~0.3). Stable and realistic sub-regional and monthly flux estimates for the western region of AB+SK can be obtained, but not for the eastern region of ON without excluding a poorly simulated station. This indicates a real observation-based inversion will likely work for the western region for tracers with similar temporal and spatial emission characteristics to fossil fuel CO2 [e.g. wintertime CH4 in Canada]. However, improvements are needed with the current inversion setup before a real inversion is performed for the eastern region.

Prior research has shown that delayed channel state information (CSI) severely degrades the throughput performance of multi-user (MU) multiple-input multiple-output (MIMO) transmission, resulting in a preference for single-user (SU) transmission. This paper investigates how the relative performance of MU-MIMO and SU-MIMO is affected by 1) different Doppler spectra, and 2) high-order prediction methods for channel estimation. Simulation results reveal that the often-used Jakes-Clarke spectrum is the worst case for MU performance. By evaluating the impact of other Doppler spectra and high-order channel prediction on MU-MIMO performance, we demonstrate that MU can tolerate larger CSI delays and retain its theoretical advantage over SU in practice.

This letter evaluates three quantization techniques for downlink multiple-user multiple-input multiple-output (MU-MIMO) systems with limited feedback. The required feedback bits for a specified rate loss are quantified, as well as the complexity for each technique. Furthermore, the net capacity, which incorporates the effect of the overhead, is studied. The analysis and simulation results reveal the advantages and drawbacks of each quantization method and demonstrate under what conditions to use one of them rather than the other.

[1] Arctic regional climate is influenced by the radiative impact of aerosol black carbon (BC) both in the atmosphere and deposited on the snow and ice covered surfaces. The NIES (National Institute for Environmental Studies) global atmospheric transport model was used, with BC emissions from mid-latitude fossil fuel and biomass burning source regions, to simulate BC concentrations with 16 year period. The model-simulated BC agreed well with the BC observations, including the trends and seasonality, at three Arctic sites: Alert (Nunavut, Canada), Barrow (Alaska, USA), and Zepplin, Ny-Alesund (Svalbard, Norway). The equivalent black carbon (EBC, absorption inferred BC) observations at the three Arctic locations showed an overall decline of 40% from 1990 to 2009; with most change occurring during early 1990s. Model simulations confirmed declining influence on near surface BC contribution by 70% , and atmospheric BC burden by one half from the Former Soviet Union (FSU) BC source region over 16 years. In contrast, the BC contribution from the East Asia (EA) region has little influence at the surface but atmospheric Arctic BC burden increased by 3 folds. Modelled dry deposition is dominant in the Arctic during wintertime, while wet deposition prevails at all latitudes during summer. Sensitivity analyses on the dry and wet deposition schemes indicate that parameterizations need to be refined to improve on the model performance. There are limitations in the model due to simplified parameterizations and remaining model uncertainties, which requires further exploration of source region contributions, especially from growing EA source region to Arctic BC levels in the future is warranted.

mmWave (millimeter-Wave) is a very promising technology for the future wireless communication. To mitigate its high attenuation characteristics, mmWave communication frequently employs directional beamforming for both transmission and reception. Localization commonly takes advantage of directionality in RF frequencies in urban and indoor environments. In this paper, we use lessons learned from classical RF-based localization for discussing a set of feasible localization approaches in the context of mmWave bands. We further map the requirements of each discussed localization approach to design requirements for future mmWave devices and assess the expected accuracy of such approaches for a set of realistic scenarios. Our results show that mmWave-based localization is promising in both its availability and accuracy, even in the presence of a limited number of localization anchor nodes.

A new model for greenhouse gas transport has been developed based on Environment and Climate Change Canada's operational weather and environmental prediction models. When provided with realistic posterior fluxes for CO2, the CO2 simulations compare well to NOAA's CarbonTracker fields, and to near surface continuous measurements, columns from the Total Carbon Column Observing Network (TCCON), and NOAA aircraft profiles. This coupled meteorological and tracer transport model is used to study the atmospheric modulation of CO2 transport. The predictability of CO2 due to initial state sensitivity is shorter than that for the temperature field but is consistent with the predictability of the wind fields. However, when broken down into spatial scales, CO2 has predictability at the very largest scales due to long time scale memory in surface CO2 fluxes as well as in land and ocean surface forcing of meteorological fields. The predictability due to the land and ocean surface is most evident in boreal summer when biospheric uptake produces large spatial gradients in the CO2 field. Predictability errors provide an upper limit for errors arising solely from the use of uncertain meteorological analyses. When considering meteorological analysis errors, CO2 can be defined only on large scales. Thus, there is a spatial scale below which information cannot be obtained simply due to the fact that meteorological analyses are imperfect. Compared to the spatial scales resolvable in the context of imperfect atmospheric analyses, the differences between two sets of posterior fluxes are resolvable only for very large scales. Similarly, the impact of convective tracer transport exceeds that due to atmospheric analysis errors for only the largest spatial scales.

Dientamoeba fragilis is a potentially pathogenic, enteric, protozoan parasite with a worldwide distribution. While clinical case reports and prevalence studies appear regularly in the scientific literature, little attention has been paid to this parasite’s biology, life cycle, host range, and possible transmission routes. Overall, these aspects of Dientamoeba biology remain poorly understood at best. In this study, a total of 420 animal samples, collected from Australia, were surveyed for the presence of Dientamoeba fragilis using PCR. Several PCR assays were evaluated for sensitivity and specificity. Two previously published PCR methods demonstrated cross reactivity with other trichomonads commonly found in animal samples. Only one assay exhibited excellent specificity. Using this assay D. fragilis was detected from one dog and one cat sample. This is the first report of D. fragilis from these animals and highlights the role companion animals may play in D. fragilis transmission. This study demonstrated that some published D. fragilis molecular assays cross react with other closely related trichomonads and consequently are not suitable for animal prevalence studies.

Independent verification of bottom-up greenhouse gas (GHG) emission inventories is crucial for a reliable reporting of Kyoto gases to the United Nations Framework Convention on Climate Change. Here, we use a pseudo-data experiment to test if our improved version of the well-known Radon tracer method (RTM) is able to quantitatively retrieve regional GHG fluxes. Using in-situ observations in Egbert, Canada, from 2006 to 2009 for the RTM, we derive night-time fluxes of CH4 and N2O in southern Ontario. The N2O fluxes found have a inter-quartile range of 7.6–31.2 μgN2O/(m2h) with an overall mean of 24.4 ± 5.6 μgN2O/(m2h). Comparison with the EDGAR4.1 inventory revealed an underestimation by a factor of 1.7 ± 0.4 in the inventory, which is explainable by missing natural sources and a missing seasonal cycle in the inventory. Our RTM-based fluxes of CH4 with a inter-quartiles range of 0.19–0.49 mgCH4/(m2h) and a mean of 0.36 ± 0.08 mgCH4/(m2h) lie significantly below the inventory-based estimates of 0.79 ± 0.06 m...

An orthogonal frequency division multiplexing system suffers performance degradation when the length of the cyclic prefix is less than the channel impulse response. The root cause of this degradation is the inter-carrier interference (ICI) and inter-symbol interference (ISI) introduced by the excessive multipath delay. Generally, multiple-input multiple-output (MIMO) beamforming is helpful in mitigating such interference because it can spatially suppress some of the multipath. However, the effectiveness of this suppression is very limited. In this paper, we propose an ICI/ISI-aware beamforming algorithm which explicitly takes into account the multipath characteristic of the channel. Optimal steering vectors are derived to maximize the signal-to-interference-plus-noise ratio. This technique not only achieves the beamforming benefit, but also significantly mitigates the ICI and ISI. We show, via simulations, that the proposed algorithm can dramatically reduce the block error rate, permitting good performance for channel delay profiles that would break conventional links. This is vitally important for the extension of indoor wireless LAN designs to outdoor uses.

A 4-day-old neonate born prematurely at 29 weeks gestation developed thrombocytopenia (platelet count 43 × 109/L) with associated severe pulmonary and intracranial hemorrhaging. Urgent transfusions with 10 mL/kg of packed red cells and 10 mL/kg of platelet concentrate were given. These were sourced from blood donated 2 days earlier in Singapore by a 21-year-old female university student who was clinically well at the time. The day after these blood products were given to the neonate, the blood donor contacted the blood transfusion service to inform them that she was now sick with a febrile flu-like illness. Her blood donation screening plasma sample was retrieved and tested by PCR for several viruses, including dengue, chikungunya, enterovirus, and Epstein-Barr virus. Dengue RNA (serotype 2) was found to be present at a very low amount (i.e., at a real-time PCR cycle Ct number of 39–40) (Fig. 1A⇓ ) from the initial RNA extract (extract A). To confirm the presence of this low amount of dengue 2 RNA, the same extract (extract A, which had been stored at −20 °C) was retested (Fig. 1B⇓ ), and again found to give a low-positive result. Figure 1. Real-time dengue RNA PCR outputs for the donor plasma sample. (A), Real-time PCR results on the RNA extract (extract A, first test) obtained from the first donor sample showing a Ct of 39.6, a low-level positive signal for dengue serotype 2 RNA. (B), Repeat testing on extract A after 1 cycle of freeze-thawing (from −20 °C), showing a higher Ct of 40.8, indicating an even lower amount of RNA present. The normal real-time PCR output is seen as a sigmoidal plot. The Ct value is where the signal sigmoid curve (indicating accumulation of the specific dengue PCR product) crosses the threshold (green horizontal line) indicating a positive …

We report a pseudo-outbreak of Rhizobium radiobacter infections resulting from contamination by a saline dispenser in the microbiology laboratory. Isolates from clinical specimens had identical antimicrobial susceptibilities and electrophoretic fingerprints. The episode resolved with autoclaving of the dispenser. This demonstrates the importance of timely, thorough investigation of unusual organisms, particularly when they appear as a cluster.

Land surface models (LSMs) need to be coupled with atmospheric general circulation models (GCMs) to adequately simulate the exchanges of energy, water, and carbon between the atmosphere and terrestrial surfaces. The heterogeneity of the land surface and its interaction with temporally and spatially varying meteorological conditions result in nonlinear effects on fluxes of energy, water, and carbon, making it challenging to scale these fluxes accurately. The issue of up-scaling remains one of the critical unsolved problems in the parameterization of subgrid-scale fluxes in coupled LSM and GCM models. A new distributed LSM, the Ecosystem–Atmosphere Simulation Scheme (EASS) was developed and coupled with the atmospheric Global Environmental Multiscale model (GEM) to simulate energy, water, and carbon fluxes over Canada’s landmass through the use of remote sensing and ancillary data. Two approaches (lumped case and distributed case) for handling subgrid heterogeneity were used to evaluate the effect of land-cover heterogeneity on regional flux simulations based on remote sensing. Online runs for a week in August 2003 provided an opportunity to investigate model performance and spatial scaling issues. Comparisons of simulated results with available tower observations (five sites) across an east–west transect over Canada’s southern forest regions indicate that the model is reasonably successful in capturing both the spatial and temporal variations in carbon and energy fluxes, although there were still some biases in estimates of latent and sensible heat fluxes between the simulations and the tower observations. Moreover, the latent and sensible heat fluxes were found to be better modeled in the coupled EASS–GEM system than in the uncoupled GEM. There are marked spatial variations in simulated fluxes over Canada’s landmass. These patterns of spatial variation closely follow vegetation-cover types as well as leaf area index, both of which are highly correlated with the underlying soil types, soil moisture conditions, and soil carbon pools. The surface fluxes modeled by the two up-scaling approaches (lumped and distributed cases) differ by 5%–15% on average and by up to 15%–25% in highly heterogeneous regions. This suggests that different ways of treating subgrid land surface heterogeneities could lead to noticeable biases in model output.

Inversion models can use atmospheric concentration measurements to estimate surface fluxes. This study is an evaluation of the errors in a regional flux inversion model for different provinces of Canada, Alberta (AB), Saskatchewan (SK) and Ontario (ON). Using CarbonTracker model results as the target, the synthetic data experiment analyses examined the impacts of the errors from the Bayesian optimisation method, prior flux distribution and the atmospheric transport model, as well as their interactions. The scaling factors for different sub-regions were estimated by the Markov chain Monte Carlo (MCMC) simulation and cost function minimization (CFM) methods. The CFM method results are sensitive to the relative size of the assumed model-observation mismatch and prior flux error variances. Experiment results show that the estimation error increases with the number of sub-regions using the CFM method. For the region definitions that lead to realistic flux estimates, the numbers of sub-regions for the western region of AB/SK combined and the eastern region of ON are 11 and 4 respectively. The corresponding annual flux estimation errors for the western and eastern regions using the MCMC (CFM) method are -7 and -3 % (0 and 8 %) respectively, when there is only prior flux error. The estimation errors increase to 36 and 94 % (40 and 232 %) resulting from transport model error alone. When prior and transport model errors co-exist in the inversions, the estimation errors become 5 and 85 % (29 and 201 %). This result indicates that estimation errors are dominated by the transport model error and can in fact cancel each other and propagate to the flux estimates non-linearly. In addition, it is possible for the posterior flux estimates having larger differences than the prior compared to the target fluxes, and the posterior uncertainty estimates could be unrealistically small that do not cover the target. The systematic evaluation of the different components of the inversion model can help in the understanding of the posterior estimates and percentage errors. Stable and realistic sub-regional and monthly flux estimates for western region of AB/SK can be obtained, but not for the eastern region of ON. This indicates that it is likely a real observation-based inversion for the annual provincial emissions will work for the western region whereas; improvements are needed with the current inversion setup before real inversion is performed for the eastern region.

Immune suppression is a recognized risk factor for necrotizing fasciitis. In patients with hematological malignancies, a profoundly immunocompromised group, the predominant causative organisms are Gram negative. Clinical presentation and outcomes in these patients are similar to the immunocompetent. The Laboratory Risk Indicator for Necrotizing Fasciitis score is not reliable for risk stratification of the disease.

© 2015 Chan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Angiostrongylus cantonensis and Angiostrongylus mackerrasae are metastrongyloid nematodes that infect various rat species. Terrestrial and aquatic molluscs are intermediate hosts of these worms while humans and dogs are accidental hosts. Angiostrongylus cantonensis is the major cause of angiostrongyliasis, a disease characterised by eosinophilic meningitis. Although both A. cantonensis and A. mackerrasae are found in Australia, A. cantonensis appears to account for most infections in humans and animals. Due to the occurrence of several severe clinical cases in Sydney and Brisbane, the need for epidemiological studies on angiostrongyliasis in this region has become apparent. In the present study, a conventional PCR and a TaqMan assay were compared for their ability to amplify Angiostrongylus DNA from DNA extracted from molluscs. The TaqMan assay was more sensitive, capable of detecting the DNA equivalent to one hundredth of a nematode larva. Therefore, the TaqMan assay was used to screen molluscs (n=500) of 14 species collected from the Sydney region. Angiostrongylus DNA was detected in 2 of the 14 mollusc species; Cornu aspersum [14/ 312 (4.5%)], and Bradybaenia similaris [1/10 (10%)], which are non-native terrestrial snails commonly found in urban habitats. The prevalence of Angiostrongylus spp. was 3.0% ±0.8% (CI 95%). Additionally, experimentally infected Austropeplea lessoni snails shed A. cantonensis larvae in their mucus, implicating mucus as a source of infection. This is the first Australian study to survey molluscs using real-time PCR and confirms that the garden snail, C. aspersum, is a common intermediate host for Angiostrongylus spp. in Sydney.

This paper evaluates and compares the performance of single- user (SU) and multi-user (MU) transmission for downlink multiple-input multiple-output (MIMO) channels in terms of system energy efficiency (EE). We introduce power control algorithms to maximize EE. Specifically, to optimize the power allocation, we consider the problem of EE maximization with the satisfaction of the minimum spectral efficiency (SE) gain. Antenna selection is taken into account to further enhance the EE performance for both SU and MU systems. Our results reveal that we should turn off extra antennas at the transmitter, which are originally used for diversity gain but incur large circuit power consumption. Our comparisons between SU and MU differ from conventional comparisons, which focus on SE. Jointly considering EE and SE, we show that SU is more desirable when the transmit power is low, while MU is favored in the case of high transmit power.

In this study we use a modified version of the ecosystem model Boreal Ecosystem Productivity Simulator (BEPS) to simulate gross primary productivity (GPP) derived from measured CO2 flux at the Takayama site, which is characterized by a broadleaf deciduous secondary forest. The period of simulation is from 1998 to 2002. The performance of the model is assessed in its ability to reproduce seasonal and inter-annual variations in the derived GPP. Given appropriate vegetation parameters and meteorological conditions for the site, we find that the model can simulate seasonal changes and inter-annual variability of GPP that are in close agreement with those derived from the eddy covariance CO2 flux measurements. Estimated annual GPPs (in gC m−2) are 1171 (1998), 1024 (1999), 1274 (2000), 1200 (2001), and 1243 (2002). (Positive GPP is defined as ecosystem assimilation of CO2.) Although the inter-annual variability of the seasonal cycle and its upward trend are simulated relatively well, the model tends to overestimate GPP, particularly from 2000 to 2002 when the measured leaf area index (LAI) during the growing season was relatively high. Furthermore, due to certain missing phenological mechanisms in the model, it tends to overestimate photosynthetic absorption during the latter half of the growing season. Also, the model does not resolve the understory of dense evergreen dwarf bamboo at the site, thus failing to catch the start of photosynthetic activity by the understory before the leaf emergence of the woody component takes place in the spring. Results indicate that the observed inter-annual variability in GPP at the Takayama site has been influenced mostly by changes in LAI.

Empyema is a problem faced by clinicians worldwide. Most cases are caused by Gram-positive organisms, such as streptococci and staphylococci. Empyema caused by Capnocytophaga spp. is extremely uncommon (H. Bonatti et al., Clin. Microbiol. Infect. 9:380–387, 2003). We present a unique case of a polymicrobial empyema, with a predominance of Capnocytophaga sputigena , in an older patient with no history of animal bite or splenectomy.

Estimating global carbon fluxes by inverting atmospheric CO2 through the use of atmospheric transport models has shown the importance of the covariance between biospheric fluxes and atmospheric transport on the carbon budget. This covariance or coupling occurs on many time scales. This study examines the coupling of the biosphere and the atmosphere on the meso- and synoptic scales using a coupled atmosphere–biosphere regional model covering Canada. The results are compared with surface and light aircraft measurement campaigns at two boreal forest sites in Canada (Fraserdale and BERMS).Associated with cold and warm frontal features, the model results showed that the biospheric fluxes are strongly coupled to the atmosphere through radiative forcing. The presence of cloud near frontal regions usually results in reduced photosynthetic uptake, producing CO2 concentration gradients across the frontal regions on the order of 10 parts per million (ppm). Away from the frontal region, the biosphere is coupled to the mesoscale variations in similar ways, resulting in mesoscale variations in CO2 concentrations of about 5 ppm.The CO2 field is also coupled strongly to the atmospheric dynamics. In the presence of frontal circulation, the CO2 near the surface can be transported to the mid to upper troposphere. Mesoscale circulation also plays a significant part in transporting the CO2 from the planetary boundary layer (PBL) to the mid-troposphere. In the absence of significant mesoscale or synoptic scale circulation, the CO2in the PBL has minimal exchange with the free troposphere, leading to strong gradients across the top of the PBL. We speculate that the ubiquity of the common synoptic and mesoscale processes in the atmosphere may contribute significantly to the rectifier effect and hence CO2 inversion calculations.DOI: 10.1111/j.1600-0889.2004.00104.x

Continuous and flask measurements of atmospheric CO 2 taken at Sable Island from August 1992 to April 1993 are presented and characterised as a function of air mass origin. The atmospheric environment over Sable Island (43°56′N, 60°01′W) is continuously influenced by the complex meteorology of synoptic systems moving off North America. This makes the interpretation of the Sable Island CO 2 data difficult. However, trajectory analysis shows distinct quantitative differences between the statistics of CO 2 measurements associated with air masses from “North America” (regions of high anthropogenic and terrestrial biospheric fluxes associated with much of the United States and the southern half of Canada) and of those associated with air masses from the “Arctic/North Atlantic” (regions of few terrestrial fluxes and oceans associated with the northern half of Canada and the Atlantic Ocean). When the continuous CO 2 data are segregated into these two trajectory sectors for the period of observation, air masses originating in the North American sector show a higher CO 2 mixing ratio by ∼2 ppm in winter and lower by ∼3 ppm in summer, compared to air masses arriving from the other sector. Furthermore, the continuous Sable Island CO 2 measurements show a detectable monthly mean (August/September) diurnal cycle with an amplitude of ∼2 ppm, with a minimum occurring on average around noon local time. Given the timing of the observed diurnal minimum and the lack of vegetation on the island, this indicates that the diurnal pattern observed at Sable Island is a diffused remnant of diurnal cycles transported from the main North American continent. These characteristic details are not captured by the discrete flask sampling program on the island. DOI: 10.1034/j.1600-0889.2003.00051.x

A user scheduling problem for downlink multiuser-multiple-input-multiple-output (MU-MIMO) systems is investigated. Unlike in theoretical analysis, users are usually equipped with different numbers of antennas in practical downlink systems, which we call receive antenna heterogeneity. We propose a scheduling algorithm which utilizes the property of receiver antenna heterogeneity to improve the system's throughput. The algorithm consists of two strategies: (1) divide the whole set of users into several groups where each group contains multiple users served simultaneously; (2) allocate spatial streams to users in each group such that sum rate is maximized. Simulation results are provided to show that our algorithm outperforms the homogeneous scheduling algorithm which does not take the heterogeneity into account.