Mitigating nitrogen pollution from global croplands with cost-effective measures

Cropland is one of the major sources of global nitrogen pollution1, 2. Mitigating nitrogen pollution from global croplands is a grand challenge because of the nature of non-point source pollution from millions of farms and the lack of financial resources and scientific knowledge of farmers3. Here we synthesize 683 studies worldwide and identify 11 key measures which can reduce 30-70% of nitrogen pollution while increasing crop yield and nitrogen use efficiency by 10-30% and 20-60%, respectively. Adoption of these measures would produce 14 million tonnes (Tg) more crop nitrogen with 28 Tg less nitrogen fertilizer and 27 Tg less nitrogen pollution to the environment in global croplands in 2015. However, to achieve these potentials, innovative policies such as a nitrogen credit system (NCS) should be implemented to incentivize and subsidize the adoption of these measures given the mismatch between benefits for the whole society while the abatement cost only for farmers. Full implementation of the best-fitted measures could achieve 306 billion USD benefits on ecosystem, human health and climate globally, with net mitigation costs of only 21 billion USD given 35 billion USD fertilizer saving cost has offset 2/3 of the total mitigation cost. The large benefit-to-cost ratio suggests the feasibility and urgency to implement the NCS and Tier approaches could help to implement the most cost-effective measures on regional and local scales.

Chest computed tomography and chest X-ray in the diagnosis of community-acquired pneumonia: a retrospective observational study

Objectives To compare the yield of early combined use of chest X-ray (CXR) and chest computed tomography (CT) in patients diagnosed with community-acquired pneumonia (CAP) presenting to the emergency department (ED) and assess the impact of chest CT on the initial diagnosis. Methods The medical records of 900 patients who presented to the ED and were diagnosed with CAP over a 1-year period were reviewed, and 130 patients who underwent CXR and chest CT within 48 hours were selected. CXR findings were classified as positive, negative, or inconclusive for CAP. Chest CT findings were defined as positive, negative, inconclusive, or positive with add-on to the CXR findings. CT was classified as having no benefit, large benefit, or moderate benefit based on the chest CT and CXR findings. Results Chest CT results were positive in 90.7% of patients, with 41.5% being newly diagnosed after negative or inconclusive CXR and 21.5% being diagnosed with add-on to the CXR findings. CT had large, moderate, and no benefit over CXR in diagnosing or excluding CAP in 45.3%, 21.5%, and 33.1% of patients, respectively. Conclusion Early chest CT may be used to compliment CXR in the early diagnosis of CAP among patients in the ED.

Vertebroplasty for osteoporotic vertebral fracture

Appropriate care of patients with a recent painful osteoporotic vertebral fracture (VF) requires immobilisation, analgesics and spinal orthoses. Some VFs are however responsible for disabling pain and prolonged bed rest. In this context, vertebroplasty techniques have been proposed with a large benefit in case series and open-label randomised studies, but lack efficacy in three among four double-blind randomised studies. The objectives of the treatment of a recent painful VF are to relieve pain and to preserve mechanical conditions. With this in mind, we report an experts’ opinion paper on the indications for vertebroplasty and research agenda for clinical studies.

The conceptual of re-design propulsion system and ship electricity management to reduce waste emission

Climate change is a serious threat to the environment and socioeconomic globally. Climate change is caused by natural processes and due to human activities that have resulted in long-term climate fluctuations and even globally over the past few decades, the climate has experienced a fairly rapid rise in average temperatures. Climate change is mainly caused due to ozone depletion which results in changes in greenhouse effect conditions. The International Maritime Organization (IMO) has adopted standards to reduce sulfur pollution from ships. The majority of naval warships today use conventional mechanical propulsion systems where the power from the main propulsion is transmitted to the propeller through gearboxes. The ships owned by the Navy almost all still use conventional thrust systems with diesel engine starters. With a conventional support system. The latest innovation in the support system that has been carried out, namely on the United States Navy warship TAKE-1 (the destroyer ship), whereby changing the support system from conventional to electricity with the concept of Integrated Fully Electric Propulsion (IFEP) can reduce fuel use by 10% to 25%. IFEP application if applied to ships of the Navy, will obtain a very large benefit in overcoming environmental problems namely reducing air pollution.

Population size mediates the contribution of high-rate and large-benefit mutations to parallel evolution

Both mutations with large benefits and mutations occurring at high rates may cause parallel evolution, but their contribution is expected to depend on population size. We show that small and large bacterial populations adapt to a novel antibiotic using similar numbers, but different types of mutations. Small populations repeatedly substitute similar high-rate structural variants, including the deletion of a nonfunctional β-lactamase, and evolve modest resistance levels. Hundred-fold larger populations more frequently use the same low-rate, large-benefit point mutations, including those activating the β-lactamase, and reach 50-fold higher resistance levels. Our results demonstrate a key role of clonal interference in mediating the contribution of high-rate and large-benefit mutations in populations of different size, facilitated by a tradeoff between rates and fitness effects of different mutation classes.

Comparing Paper and Digital Procedure Formats: Different Attitudes, Quality Perceptions and Deviations

Operating procedures are an integral part of the high-risk industries such as the Oil & Gas industry. Workers need them as a tool to help complete tasks effectively, efficiently, and safely and in the intended manner (Amyotte et al, 2007). Often, the assumption in the process safety domain is that procedures are very high quality, if not perfect, and therefore workers must follow them rigidly. What is all too often the case is that workers encounter a number of issues with procedure quality (e.g., inaccurate information, outdated steps; Hendricks & Peres, under review; Sasangohar et al., 2018). These quality issues have been shown to be associated with more deviations (Hendricks & Peres, under review). Now that many in the industry are starting to move toward digital procedures (hand-held, interactive, not .pdfs), there needs to be an examination of not only these issues, but also attitudes regarding procedure compliance and utility since these are related to deviations and also procedure use (Hendricks & Peres, under review). Accordingly, this study sought to answer the question—are workers’ perceptions of quality, attitudes, and deviation behavior different based on procedure format (digital vs. paper)? Our study consisted of 32 chemical processing and logistics workers at a large, multi-national corporation. Half of the participants ( n = 16) were already using digital procedures and the other half had not experienced a digital procedure roll-out. We were able to make both within and between- subject comparisons with the data since those digital users also still used paper for other tasks. For the within-subjects level of analysis (LOA), workers had significantly poorer quality perceptions of paper format procedures than digital procedures. Although not significantly different, workers reported more deviations for paper procedures. For the between- subjects LOA, procedure quality perceptions were significantly worse for paper procedures (paper only group) when compared to digital procedures in the digital rollout group. Deviations, utility attitude, and compliance attitude were not significantly different for the two formats (better attitudes regarding utility, poorer attitudes regarding compliance, fewer deviations for digital) and the effect sizes were at or above medium. We think it is important to start this line of research in the process safety industries because if the transition to digital procedures is already occurring, we need evidence that it is justifiable by demonstrating—especially at different LOAs—that we can expect improvements in these critical procedure-related variables. We need to expand this line of research to other companies, and to multiple sites with larger samples. Indeed, one of the challenges is gaining access to such important workers, but we see a large benefit to organizations who ultimately will be investing many resources into these types of changes.

Maximally Localized Dynamical Quantum Embedding for Solving Many-Body Correlated Systems

We present a quantum embedding methodology to resolve the Anderson impurity model in the context of dynamical mean-field theory, based on an extended exact diagonalization method. Our method provides a maximally localized quantum impurity model, where the non-local components of the correlation potential remain minimal. This comes at a large benefit, as the environment used in the quantum embedding approach is described by propagating correlated electrons and hence offers an exponentially increasing number of degrees of freedom for the embedding mapping, in contrast to traditional free-electron representation where the scaling is linear. We report that quantum impurity models with as few as 3 bath sites can reproduce both the Mott transition and the Kondo physics, thus opening a more accessible route to the description of time-dependent phenomena. Finally, we obtain excellent agreement for dynamical magnetic susceptibilities, poising this approach as a candidate to describe 2-particle excitations such as excitons in correlated systems. We expect that our approach will be highly beneficial for the implementation of embedding algorithms on quantum computers, as it allows for a fine description of the correlation in materials with a reduced number of required qubits.

Priority Actions to Advance Population Sodium Reduction

High sodium intake is estimated to cause approximately 3 million deaths per year worldwide. The estimated average sodium intake of 3.95 g/day far exceeds the recommended intake. Population sodium reduction should be a global priority, while simultaneously ensuring universal salt iodization. This article identifies high priority strategies that address major sources of sodium: added to packaged food, added to food consumed outside the home, and added in the home. To be included, strategies needed to be scalable and sustainable, have large benefit, and applicable to one of four measures of effectiveness: (1) Rigorously evaluated with demonstrated success in reducing sodium; (2) suggestive evidence from lower quality evaluations or modeling; (3) rigorous evaluations of similar interventions not specifically for sodium reduction; or (4) an innovative approach for sources of sodium that are not sufficiently addressed by an existing strategy. We identified seven priority interventions. Four target packaged food: front-of-pack labeling, packaged food reformulation targets, regulating food marketing to children, and taxes on high sodium foods. One targets food consumed outside the home: food procurement policies for public institutions. Two target sodium added at home: mass media campaigns and population uptake of low-sodium salt. In conclusion, governments have many tools to save lives by reducing population sodium intake.

Modeling of Conduction and Switching Losses for IGBT and FWD Based on SVPWM in Automobile Electric Drives

The modeling of conduction and switching losses for insulated gate bipolar transistors (IGBTs) and free-wheeling diodes (FWDs) in automobile applications is becoming increasingly important, especially for the improvement of the system efficiency and the reliability prediction. The traditional modeling of conduction and switching losses based on the space vector pulse width modulation (SVPWM) is not applicable in practice due to the complex curve-fitting and the computation demands. In this paper, a simple and practical losses model for IGBTs and FWDs is proposed based on the SVPWM algorithm. Firstly, the traditional power losses model is introduced briefly. Then, the piecewise linear switching losses model and the conduction losses model based on the equivalent three-order harmonic model of the duty cycle are proposed. The comparison of experimental results between the traditional model and the proposed model is presented in the experiment validation. Furthermore, the power analyzer is adopted to measure the inverter losses, and the chips losses are further validated when other extra losses are considered. The proposed model shows good modeling accuracy with the large benefit of smaller measurement and lower computation requirements.

Optimized multiple testing procedures for nested sub-populations based on a continuous biomarker

An important step in the development of targeted therapies is the identification and confirmation of sub-populations where the treatment has a positive treatment effect compared to a control. These sub-populations are often based on continuous biomarkers, measured at baseline. For example, patients can be classified into biomarker low and biomarker high subgroups, which are defined via a threshold on the continuous biomarker. However, if insufficient information on the biomarker is available, the a priori choice of the threshold can be challenging and it has been proposed to consider several thresholds and to apply appropriate multiple testing procedures to test for a treatment effect in the corresponding subgroups controlling the family-wise type 1 error rate. In this manuscript we propose a framework to select optimal thresholds and corresponding optimized multiple testing procedures that maximize the expected power to identify at least one subgroup with a positive treatment effect. Optimization is performed over a prior on a family of models, modelling the relation of the biomarker with the expected outcome under treatment and under control. We find that for the considered scenarios 3 to 4 thresholds give the optimal power. If there is a prior belief on a small subgroup where the treatment has a positive effect, additional optimization of the spacing of thresholds may result in a large benefit. The procedure is illustrated with a clinical trial example in depression.