Application of processed organic municipal solid waste on agricultural land - a scenario analysis

Source separation, composting and anaerobic digestion, with associated land application, are increasingly being considered as alternative waste management strategies to landfilling and incineration of municipal solid waste (MSW). Environmental life cycle assessments are a useful tool in political decision-making about waste management strategies. However, due to the diversity of processed organic MSW and the situations in which it can be applied, the environmental impacts of land application are very hard to determine by experimental means. In the current study, we used the agroecosystem model Daisy to simulate a range of different scenarios representing different geographical areas, farm and soil types under Danish conditions and legislation. Generally, the application of processed organic MSW resulted in increased emissions compared with the corresponding standard scenarios, but with large differences between scenarios. Emission coefficients for nitrogen leaching to the groundwater ranged from 0.03 to 0.87, while those for nitrogen lost to surface waters through tile drains ranged from 0 to 0.30. Emission coefficients for N2O formation ranged from 0.013 to 0.022 and for ammonia volatilization from 0.016 to 0.11. These estimates are within reasonable range of observed values under similar conditions. Furthermore, a sensitivity analysis showed that the estimates were not very sensitive to the mineralization dynamics of the processed organic MSW. The results show that agroecosystem models can be powerful tools to estimate the environmental impacts of land application of processed MSW under different conditions. Despite this, agroecosystem models have only been used to a very limited degree for this purpose

Just-in-time assembly of cell-cycle protein complexes

Our comparative analysis of eukaryotic cell-cycle complexes reveals that the identity of the periodically expressed subunits differs significantly between organisms and is often mirrored by changes in cell-cycle-dependent phosphorylation of the protein products. This indicates that many different solutions have evolved for just-in-time assembly of the same molecular machines

Seasonal Affective Disorder: SAD or Fad?

Seasonal affective disorder (SAD) and phototherapy have recently been the subject of a great deal of interest in the psychiatric literature. First described in 1984 (I), SAD is now defined as a cyclic illness characterized by recurrent episodes of fall/winter depression alternating with periods of spring/summer euthymia (normal mood) or hypomania (mild elation and behavioral activation) (2) . Recent findings indicate that there may be at least two additional patterns of seasonal depressions, one characterized by annual summer depressions with euthyrnic, hypomanic or manic symptoms in the winter, and the other characterized by depressive episodes occurring in both winter and summer (3-6)

Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics

We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond (h3JNC') spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to refine protein structures to this agreement. The ProCS method thus offers a powerful new tool for refining the structures of hydrogen bonding networks to high accuracy with many potential applications such as protein flexibility in ligand binding.Comment: PLOS ONE accepted, Nov 201

Relational Fusion Networks: Graph Convolutional Networks for Road Networks

The application of machine learning techniques in the setting of road networks holds the potential to facilitate many important intelligent transportation applications. Graph Convolutional Networks (GCNs) are neural networks that are capable of leveraging the structure of a network. However, many implicit assumptions of GCNs do not apply to road networks. We introduce the Relational Fusion Network (RFN), a novel type of GCN designed specifically for road networks. In particular, we propose methods that outperform state-of-the-art GCNs by 21%-40% on two machine learning tasks in road networks. Furthermore, we show that state-of-the-art GCNs may fail to effectively leverage road network structure and may not generalize well to other road networks.Comment: IEEE Transactions on Intelligent Transportation Systems (2020). arXiv admin note: substantial text overlap with arXiv:1908.1156

The emission consequences of using biodiesel and bio ethanol as a fuel for road transport in Denmark

This article explains the emission consequences of using biodiesel and bio ethanol as a fuel for road transport in Denmark calculated in the REBECa project. For the years 2004, 2010, 2015, 2020, 2025 and 2030, two fossil fuel baseline scenarios (FS) are considered characterised by different traffic growth rates. For each FS, two biofuel scenarios (BS1, BS2) are considered with a 5.75 % biodiesel/bio ethanol share in 2010 as a common starting point. From 2010, linear growths are assumed for BS1 (10 % in 2020) and BS2 (25 % in 2030). The emissions presented in this study are vehicle based; a separate Well to Wheels (W-t-W) assessment of the total emission consequences of producing and using biofuels has been conducted in a different part of REBECa. The maximum CO2 emission difference between FS and BS2 becomes 26 % in 2030. The NOx and VOC emission variations between FS and both biofuel scenarios are 3 % or less. For CO and TSP the largest emission differences, 5 % and -12 %, respectively, occur between the FS and BS2 scenarios in 2030. The biofuel emission impacts are insignificant for NOx,VOC, CO and TSP compared to the generally large emission reductions predicted in all scenarios driven by the gradual strengthened emission standards for new vehicles, by far outweighing the emission influence from biofuels and traffic growth. The emission estimates for NOx, VOC, CO and TSP presented in this study are less certain than for CO2 due to the relatively scarce biofuel emission data implemented in the calculations. As a consequence, the obtained emission results must be assessed with care. Bearing in mind these uncertainties, the calculation approach for emissions from biofuel usage presented in this study can be used as a tool to carry out sensitivity analysis, environmental impact assessment studies, or for research purposes as such

The resection angle in apical surgery: a CBCT assessment.

OBJECTIVES The primary objective of the present radiographic study was to analyse the resection angle in apical surgery and its correlation with treatment outcome, type of treated tooth, surgical depth and level of root-end filling. MATERIALS AND METHODS In the context of a prospective clinical study, cone beam computed tomography (CBCT) scans were taken before and 1 year after apical surgery to measure the angle of the resection plane relative to the longitudinal axis of the root. Further, the surgical depth (distance from the buccal cortex to the most lingual/palatal point of the resection plane) as well as the level of the root-end filling relative to the most coronal point of the cut root face was determined. Treated teeth were categorized into four groups (maxillary and mandibular anterior and posterior teeth). The final material comprised 62 treated roots in 55 teeth. RESULTS The mean calculated resection angle of all roots was 17.7° ± 11.4° (range -9.6° to 43.4°). Anterior maxillary roots presented the highest mean angle (25.8° ± 10.3°) that was significantly different from the mean angle in posterior maxillary roots (10.7° ± 9.4°; p 20°), however without reaching statistical significance (p = 0.0905). Angles did not correlate either with the surgical depth or with the retrofilling length. CONCLUSIONS Statistically significant differences were observed comparing resection angles of different tooth groups. However, the angle had no significant effect on treatment outcome. CLINICAL RELEVANCE Contrary to common belief, the resection angle in maxillary anterior teeth was greater than in the other teeth. The surgeon is advised to pay attention to the resection angle when bevelling maxillary anterior teeth in apical surgery

The Emission consequences of using biodiesel and bio ethanol as a fuel for road transport in Denmark

This article explains the emission consequences of using biodiesel and bio ethanol as a fuel for road transport in Denmark calculated in the REBECa project. For the years 2004, 2010, 2015, 2020, 2025 and 2030, two fossil fuel baseline scenarios (FS) are considered characterised by different traffic growth rates. For each FS, two biofuel scenarios (BS1, BS2) are considered with a 5.75 % biodiesel/bio ethanol share in 2010 as a common starting point. From 2010, linear growths are assumed for BS1 (10 % in 2020) and BS2 (25 % in 2030). The emissions presented in this study are vehicle based; a separate Well to Wheels (W-t-W) assessment of the total emission consequences of producing and using biofuels has been conducted in a different part of REBECa. The maximum CO2 emission difference between FS and BS2 becomes 26 % in 2030. The NOx and VOC emission variations between FS and both biofuel scenarios are 3 % or less. For CO and TSP the largest emission differences, 5 % and -12 %, respectively, occur between the FS and BS2 scenarios in 2030. The biofuel emission impacts are insignificant for NOx,VOC, CO and TSP compared to the generally large emission reductions predicted in all scenarios driven by the gradual strengthened emission standards for new vehicles, by far outweighing the emission influence from biofuels and traffic growth. The emission estimates for NOX, VOC, CO and TSP presented in this study are less certain than for CO2 due to the relatively scarce biofuel emission data implemented in the calculations. As a consequence, the obtained emission results must be assessed with care. Bearing in mind these uncertainties, the calculation approach for emissions from biofuel usage presented in this study can be used as a tool to carry out sensitivity analysis, environmental impact assessment studies, or for research purposes as such