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Large-scale hydrological models (LHMs) are commonly used for regional and global assessment of future water shortage outcomes under climate and socioeconomic scenarios. The irrigation of croplands, which accounts for the lion's share of human water consumption, is critical in understanding these water shortage trajectories. Despite irrigation's defining role, LHM frameworks typically impose trajectories of land use that underlie irrigation demand, neglecting potential dynamic feedbacks in the form of human instigation of and subsequent adaptation to water shortages via irrigated crop area changes. We extend an LHM, MOSART-WM, with adaptive farmer agents, applying the model to the continental United States to explore water shortage outcomes that emerge from the interplay between hydrologic-driven surface water availability, reservoir management, and farmer irrigated crop area adaptation. The extended modeling framework is used to conduct a hypothetical computational experiment comparing differences between a model run with and without the incorporation of adaptive farmer agents. These comparative simulations reveal that accounting for farmer adaptation via irrigated crop area changes substantially alters modeled water shortage outcomes, with US-wide annual water shortages being reduced by as much as 42 % when comparing adaptive and non-adaptive versions of the model forced with US climatology from the period 1950–2009.

Carbapenem resistance due to metallo-beta-lactamases (MBLs) is a global phenomenon and an important challenge for antibiotic therapy (Boyd et al., 2020 [1]). While previous reports have demonstrated both in vitro and in vivo synergy using the combination of ceftazidime-avibactam and aztreonam against Stenotrophomonas maltophilia, an MBL-harboring organism, this treatment strategy has not been reported during pregnancy (Mojic et al., 2017 [2], [3], Mojica et al., 2016 [4], Alexander et al., 2020 [5]). We describe a 33-year-old pregnant female with polymicrobial, bilateral pyelonephritis caused by Stenotrophomonas maltophilia and other gram-negative bacteria. The organisms were eradicated with the combination of ceftazidime-avibactam and aztreonam followed by successful delivery with no observed adverse effects in either mother or child post-partum.

Although super-resolution techniques based on deep neural networks (SRDNN) have drawn significant interest and numerous algorithms have been proposed, they still have reliability problems and produce artefacts when applied to new datasets. In this paper, the working mechanisms of SRDNN techniques are analyzed in terms of data mapping. Since most SRDNN techniques can be viewed as dynamic linear projections, we analyzed a large number of projection vectors (over 70 million) and found that the SRDNN method performs one-to-one mapping-like operations and may be vulnerable to unknown data patterns. Then, we applied several SRDNN techniques to real-world images and analyzed the output images. The current SRDNN methods failed to distinguish the blurred edges/lines due to low resolutions from coding artefacts and enhanced both, even though the SRDNN methods were trained using compressed low-resolution (LR) images. These analyses and results indicate that current SRDNN methods may not be able to provide robust performance and new structures may be necessary for reliable super-resolution performance.

Although DCN-based super-resolution (DCN-SR) techniques have shown impressive performance, the working mechanism has not been completely understood and DCN-SR methods still produce some artefacts. In this paper, we analyze the working mechanisms of DCN-SR methods. We derive mathematical formulations of the DCN-SR methods and provide some experimental analyses, which show that the effective receptive fields of the DCN-SR methods are considerably smaller than the theoretical receptive fields. Based on the mathematical formulations, experiments were performed. The results indicates that current DCN-SR methods may have some fundamental problems and new types of DCN structures are needed for reliable super-resolution performance.

Granulicatella adiacens, a nutritionally variant streptococci (NVS) is a well described organism associated with endocarditis. Previously communicated cases have documented the use of double beta-lactam therapy with ampicillin and ceftriaxone to treat patients with infective endocarditis due to Enterococcus faecalis and Streptocossus pneumoniae. We describe the first case of Granulicatella adiacens infective endocarditis in a patient successfully treated with the combination of intravenous ampicillin and ceftriaxone and document their synergistic activity.

Although gastroenteritis is the most commonly described manifestation of Edwardsiella tarda infection, the pathogenesis and transient or long-term colonization of the gastrointestinal tract of this organism in human disease is not clear. We describe a rare manifestation of E. tarda infection in a perihepatic abscess in the setting of a patient with perforated cholecystitis and its successful eradication following antibiotic treatment.

Research on choirs and other forms of group singing has been conducted for several decades and there has been a recent focus on the potential health and well-being benefits, particularly in amateur singers. Experimental, quantitative, and qualitative studies show evidence of a range of biopsychosocial and well-being benefits to singers; however, there are many challenges to rigor and replicability. To support the advances of research into group singing, the authors met and discussed theoretical and methodological issues to be addressed in future studies. The authors are from five countries and represent the following disciplinary perspectives: music psychology, music therapy, community music, clinical psychology, educational and developmental psychology, evolutionary psychology, health psychology, social psychology, and public health. This article summarizes our collective thoughts in relation to the priority questions for future group singing research, theoretical frameworks, potential solutions for design and ethical challenges, quantitative measures, qualitative methods, and whether there is scope for a benchmarking set of measures across singing projects. With eight key recommendations, the article sets an agenda for best practice research on group singing.

We compare in situ measurements of ozone (O3) and carbon monoxide (CO) profiles from the CARIBIC program with the results from the regional chemistry transport model (WRF-Chem) to investigate the role of local and regional emissions and long-range transport over southern India during the summer monsoon of 2008. WRF-Chem successfully reproduces the general features of O3 and CO distributions over the South Asian region. However, absolute CO concentrations in the lower troposphere are typically underestimated. Here we investigate the influence of local relative to remote emissions through sensitivity simulations. The influence of 50 % increased CO emissions over South Asia leads to a significant enhancement (upto 20 % in July) in upper tropospheric CO in the northern and central Indian regions. Over Chennai in southern India, this causes a 33 % increase in surface CO during June. However, the influence of enhanced local and regional emissions is found to be smaller (5 %) in the free troposphere over Chennai, except during September. Local to regional emissions are therefore suggested to play a minor role in the underestimation of CO by WRF-Chem during June–August. In the lower troposphere, a high pollution (O3: 146.4 ± 12.8, CO: 136.4 ± 12.2 nmol mol−1) event (15 July 2008), not reproduced by the model, is shown to be due to transport of photochemically processed air masses from the boundary layer in southern India. A sensitivity simulation combined with backward trajectories indicates that long-range transport of CO to southern India is significantly underestimated, particularly in air masses from the west, i.e., from Central Africa. This study highlights the need for more aircraft-based measurements over India and adjacent regions and the improvement of global emission inventories.

The aerosol optical depth (AOD) trend between 2001 and 2010 is estimated globally and regionally from observations and results from simulations with the EMAC (ECHAM5/MESSy Atmospheric Chemistry) model. Although interannual variability is applied only to anthropogenic and biomass-burning emissions, the model is able to quantitatively reproduce the AOD trends as observed by the MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor, while some discrepancies are found when compared to MISR (Multi-angle Imaging SpectroRadiometer) and SeaWIFS (Sea-viewing Wide Field-of-view Sensor) observations. Thanks to an additional simulation without any change in emissions, it is shown that decreasing AOD trends over the US and Europe are due to the decrease in the emissions, while over the Sahara Desert and the Middle East region, the meteorological changes play a major role. Over Southeast Asia, both meteorology and emissions changes are equally important in defining AOD trends. Additionally, decomposing the regional AOD trends into individual aerosol components reveals that the soluble components are the most dominant contributors to the total AOD, as their influence on the total AOD is enhanced by the aerosol water content.

We present decadal trend estimates of surface carbon monoxide (CO) simulated using the atmospheric chemistry general circulation model ECHAM5/MESSy (EMAC; ECHAM5 and MESSy stand for fifth-generation European Centre Hamburg general circulation model and Modular Earth Submodel System, respectively) based on the emission scenarios Representative Concentration Pathways (RCP) 8.5 for anthropogenic activity and Global Fire Emissions Database (GFED) v3.1 for biomass burning from 2001 through 2010. The spatial distribution of the modeled surface CO is evaluated with monthly data from the Measurements Of Pollution In The Troposphere (MOPITT) thermal infrared product. The global means of correlation coefficient and relative bias for the decade 2001–2010 are 0.95 and −4.29%, respectively. We also find a reasonable correlation (R = 0.78) between the trends of EMAC surface CO and full 10-year monthly records from ground-based observation (World Data Centre for Greenhouse Gases, WDCGG). Over western Europe, eastern USA, and northern Australia, the significant decreases in EMAC surface CO are estimated at −35.5 ± 5.8, −59.6 ± 9.1, and −13.7 ± 9.5 ppbv decade−1, respectively. In contrast, the surface CO increases by +8.9 ± 4.8 ppbv decade−1 over southern Asia. A high correlation (R = 0.92) between the changes in EMAC-simulated surface CO and total emission flux shows that the significant regional trends are attributed to the changes in primary and direct emissions from both anthropogenic activity and biomass burning.

The role and potential management of short-lived atmospheric pollutants such as aerosols are currently a topic of scientific and public debates. Our limited knowledge of atmospheric aerosol and its influence on the Earth's radiation balance has a significant impact on the accuracy and error of current predictions of future climate change. In the last few years, there have been several accounts of the changes in atmospheric aerosol derived from satellite observations, but no study considering the uncertainty caused by different/limited temporal sampling of polar-orbiting satellites and cloud disturbance in the trend estimates of cloud-free aerosol optical thickness (AOT). This study presents an approach to minimize the uncertainties by use of weighted least-squares regression and multiple satellite-derived AOTs from the space-born instruments, MODIS (onboard Terra from 2000 to 2009 and Aqua form 2003 to 2008), MISR (Terra from 2000 to 2010), and SeaWiFS (OrbView-2 from 1998 to 2007) and thereby provides more convincing trend estimates for atmospheric aerosols during the past decade. The AOT decreases over western Europe (i.e., by up to about −40% from 2003 to 2008). In contrast, a statistically significant increase (about +34% in the same period) over eastern China is observed and can be attributed to the increase in both industrial output and Asian desert dust.

It has become possible to retrieve the global, long-term trends of trace gases that are important to atmospheric chemistry, climate, and air quality from satellite data records that span more than a decade. However, many of the satellite remote sensing techniques produce measurements that have variable sensitivity to the vertical profiles of atmospheric gases. In the case of constrained retrievals like optimal estimation, this leads to a varying amount of a priori information in the retrieval and is represented by an averaging kernel (AK). In this study, we investigate to what extent the estimation of trends from retrieved data can be biased by temporal changes of averaging kernels used in the retrieval algorithm. In particular, the surface carbon monoxide data retrieved from the Measurements Of Pollution In The Troposphere (MOPITT) instrument from 2001 to 2010 were analyzed. As a practical example based on the MOPITT data, we show that if the true atmospheric mixing ratio is continuously 50% higher or lower than the a priori state, the temporal change of the averaging kernel at the surface level gives rise to an artificial trend in retrieved surface carbon monoxide, ranging from −10.71 to +13.21 ppbv yr−1 (−5.68 to +8.84 % yr−1) depending on location. Therefore, in the case of surface (or near-surface level) CO derived from MOPITT, the AKs trends multiplied by the difference between true and a priori states must be quantified in order to estimate trend biases.

In this study, we investigated the sensitivity of net radiative fluxes (FNET) at the top of atmosphere (TOA) to 16 selected uncertain parameters mainly related to the cloud microphysics and aerosol schemes in the Community Atmosphere Model version 5 (CAM5). We adopted a quasi-Monte Carlo (QMC) sampling approach to effectively explore the high-dimensional parameter space. The output response variables (e.g., FNET) are simulated using CAM5 for each parameter set, and then evaluated using the generalized linear model analysis. In response to the perturbations of these 16 parameters, the CAM5-simulated global annual mean FNET ranges from −9.8 to 3.5 W m−2 compared to 1.9 W m−2 with the default parameter values. Variance-based sensitivity analysis is conducted to show the relative contributions of individual parameter perturbations to the global FNET variance. The results indicate that the changes in the global mean FNET are dominated by changes in net cloud forcing (CF) within the parameter ranges being investigated. The threshold size parameter related to auto-conversion of cloud ice to snow is identified as one of the most influential parameters for FNET in CAM5 simulations. The strong heterogeneous geographic distribution of FNET variance shows that parameters have a clear localized effect over regions where they are acting. However, some parameters also have non-local impacts on FNET variance. Although external factors, such as perturbations of anthropogenic and natural emissions, largely affect FNET variance at the regional scale, their impact is weaker than that of model internal parameters in terms of simulating global mean FNET. The interactions among the 16 selected parameters contribute a relatively small portion to the total FNET variance over most regions of the globe. This study helps us better understand the parameter uncertainties in the CAM5 model, and thus provides information for further calibrating uncertain model parameters with the largest sensitivity.

Regular aerosol observations based on well-calibrated instruments have led to a better understanding of the aerosol radiative budget on Earth. In recent years, these instruments have played an important role in the determination of the increase of anthropogenic aerosols by means of long-term studies. Only few investigations regarding long-term trends of aerosol optical characteristics (e.g. aerosol optical thickness (AOT) and Ångström exponent (ÅE)) have been derived from ground-based observations. This paper aims to derive and discuss linear trends of AOT (440, 675, 870, and 1020 nm) and ÅE (440–870 nm) using AErosol RObotic NETwork (AERONET) level 2.0 spectral observations. Additionally, temporal trends of coarse- and fine-mode dominant AOTs (CdAOT and FdAOT) have been estimated by applying an aerosol classification based on accurate ÅE and Ångström exponent difference (ÅED). In order to take into account the fact that cloud disturbance is having a significant influence on the trend analysis of aerosols, we introduce a weighted least squares regression depending on two weights: (1) monthly standard deviation (σt) and (2) number of observations per month (nt). Temporal increase of FdAOTs (440 nm) prevails over newly industrializing countries in East Asia (weighted trends; +6.23% yr−1 at Beijing) and active agricultural burning regions in South Africa (+1.89% yr−1 at Mongu). On the other hand, insignificant or negative trends for FdAOTs are detected over Western Europe (+0.25% yr−1 at Avignon and −2.29% yr−1 at Ispra) and North America (−0.52% yr−1 for GSFC and −0.01% yr−1 at MD_Science_Center). Over desert regions, both increase and decrease of CdAOTs (+3.37% yr−1 at Solar_Village and −1.18% yr−1 at Ouagadougou) are observed depending on meteorological conditions.

The main purposes of the present paper are not only to investigate linear long-term trends of Aerosol Optical Thickness (AOT) at 443 and 555 nm over regions in Europe and South China, but also to show the uncertainty caused by cloud disturbance in the trend analysis of cloud-free aerosol. These research areas are the densely urbanised and often highly polluted regions. The study uses the Bremen AErosol Retrieval (BAER) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data for AOT retrievals in the specified regions from October 1997 to May 2008. In order to validate the individually retrieved AOTs and the corresponding trends, AErosol RObotic NETwork (AERONET) level 2.0 data have been used. The retrieved AOTs were in good agreement with those of AERONET (0.79 ≤ R ≤ 0.88, 0.08 ≤ RMSD ≤ 0.13). The contamination of the aerosol retrievals and/or AERONET observations by thin clouds can significantly degrade the AOT and lead to statistically non-representative monthly-means, especially during cloudy seasons. Therefore an inter-correction method has been developed and applied. The "corrected" trends for both BAER SeaWiFS and AERONET AOT were similar and showed in average a relative difference of ∼25.19%. In general terms, negative trends (decrease of aerosol loading) were mainly observed over European regions, with magnitudes up to −0.00453 and −0.00484 yr−1 at 443 and 555 nm, respectively. In contrast, the trend in Pearl River Delta was positive, most likely attributed to rapid urbanization and industrialization. The magnitudes of AOT increased by +0.00761 and +0.00625 yr−1 respectively at 443 and 555 nm.

For the determination of aerosol optical thickness (AOT) Bremen AErosol Retrieval (BAER) has been developed. Method and main features on the aerosol retrieval are described together with validation and results. The retrieval separates the spectral aerosol reflectance from surface and Rayleigh path reflectance for the shortwave range of the measured spectrum of top-of-atmosphere reflectance for wavelength less than 0.670 μm. The advantage of MERIS (Medium Resolution Imaging Spectrometer on the Environmental Satellite – ENVISAT – of the European Space Agency – ESA) and SeaWiFS (Sea viewing Wide Field Sensor on OrbView-2 spacecraft) observations is the availability of several spectral channels in the blue and visible range enabling the spectral determination of AOT in 7 (or 6) channels (0.412–0.670 μm) and additionally channels in the NIR, which can be used to characterize the surface properties. A dynamical spectral surface reflectance model for different surface types is used to obtain the spectral surface reflectance for this separation. The normalized differential vegetation index (NDVI), taken from the satellite observations, is the model input. Further surface bi-directional reflectance distribution function (BRDF) is considered by the Raman-Pinty-Verstraete (RPV) model. Spectral AOT is obtained from aerosol reflectance using look-up-tables, obtained from radiative transfer calculations with given aerosol phase functions and single scattering albedos either from aerosol models, given by model package "optical properties of aerosol components" (OPAC) or from experimental campaigns. Validations of the obtained AOT retrieval results with data of Aerosol Robotic Network (AERONET) over Europe gave a preference for experimental phase functions derived from almucantar measurements. Finally long-term observations of SeaWiFS have been investigated for 11 year trends in AOT. Western European regions have negative trends with decreasing AOT with time. For the investigated Asian region increasing AOT have been found.

Transmission of light through periodic metal films with intensity considerably exceeding that predicted by aperture theory is referred to as extraordinary optical transmission (EOT). The mechanisms responsible for this effect have been investigated intensively during the past decade. Here, we show an elegant method of visualizing the operative physical mechanisms for model resonance systems. By numerically mapping the resonance loci, modal and plasmonic mechanisms emerge clearly with delineated regions of dominance. Thus, the photonic transmission resonances are parametrically correlated with localized electromagnetic fields forming pure surface-plasmon polaritons (SPPs), coexisting plasmonic and cavity-mode (CM) states, and pure CMs. This mapping method renders a consistent picture of the transitions between photonic states in terms of key parameters. It shows how the TM1 CM seamlessly morphs into the odd SPP mode as the film thickness diminishes. Similarly, the TM0 mode converts to the even SPP mode. At the intersection of these mode curves, an EOT-free gap forms due to their interaction. On account of a reflection phase shift of a slit-guided mode, an abrupt transition of the resonance loci in the SPP/CM region is observed.

We present a review of highlights of our photometric and photo-polarimetric monitoring and mathematical modeling of interacting binary stars of different types classical, asynchronous, intermedi ate polars with 25 timescales corresponding to differ ent physical mechanisms and their combinations (part "Polar"); negative and positive superhumpers in nova-like and dwarf novae stars ("Superhumper"); symbiotic ("Symbiosis"); eclipsing variables with and without ev idence for a current mass transfer ("Eclipser") with a special emphasis on systems with a direct impact of the stream into the gainor star's atmosphere, which we propose to call "Impactors", or V361 Lyr-type stars. Other parts of the ILA project are "Stellar Bell" (pul sating variables of different types and periods - M, SR, RV Tau, RR Lyr, Delta Sct) and "New Variable".

No abstract available.

Objectives Maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) could be useful clinical parameters in monitoring many conditions including cystic fibrosis (CF). However, current protocols for undertaking the measurements lack standardization including the number of repeated attempts to achieve best values. We aimed to (a) determine the optimum number of attempts to achieve best MIP/MEP values, and (b) evaluate if the number of attempts is consistent across two different test days. Methods We analyzed data of a previous randomized controlled trial involving the effect of singing on respiratory muscle strength in 35 children with CF. On two different days (T1, T2) children performed MIP/MEP with at least ten attempts each to achieve < 10% repeatability. Results All children achieved repeatable MIP/MEP values within 10-11 attempts with 24 (68.6%) and 26 (74.3%) of these achieving best values of MIP and MEP, respectively, at attempts 6-11. Median values of the pressures by three, five, eight and all attempts significantly increased with more attempts (all p < 0.05). At T2, 56% required fewer attempts to achieve best values, but 32% required more attempts, indicating that the number of attempts required was inconsistent between test days. Conclusion It is likely that at least ten attempts (best two within < 10% variability) is required to achieve best and reliable MIP/MEP in children with CF. A larger sample size in children with CF and various conditions is required to consolidate these findings., Author(s): Wicharn Boonjindasup [sup.1] [sup.2] [sup.3] [sup.6], Anne B. Chang [sup.1] [sup.2] [sup.4], Julie M. Marchant [sup.2] [sup.4], J. Yoon Irons [sup.5], Margaret S. McElrea [sup.2] [sup.4] Author Affiliations: (1) [...]

Community-based open-to-all choirs or singing groups are popular internationally and associated with multiple health and well-being benefits. Facilitators of such groups require specific skills, attributes and knowledge. Therefore, we examined literature to identify key characteristics of group singing facilitators (GSFs) using a systematic review approach. Eighteen studies are included in the current review. These studies utilized qualitative research methods to illustrate GSFs' roles within the community context. Narrative synthesis revealed two meta-themes, namely music-related and group facilitation-related. Within both meta-themes, there were various skills, attributes and knowledge specific to GSFs, which appear to be intertwined. This analysis also revealed the complexity of group singing facilitation along with a lack of opportunities for training and support for GSFs. Further research is needed to develop and evaluate holistic learning to support GSFs with essential skills, attributes and knowledge to promote group singing in the community setting. [ABSTRACT FROM AUTHOR]