2,027 research outputs found
Social Accountability in Maternal Health Services in Selected Districts of Nepal and Gujarat, India
Preparatory Signal Detection for the EU-27 Member States under EU Burden Sharing - Advanced Monitoring Including Uncertainty (1990-2005)
This study follows up IIASA Interim Report IR-04-024 (Jonas et al., 2004), which addresses the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. The question probed was how well do we need to know net emissions if we want to detect a specified emission signal after a given time? The authors used the Protocol's Annex B countries as net emitters and referred to all Kyoto GHGs (CO2, CH4, N2O, HFCs, PFCs, and SF6) excluding CO2 emissions/removals due to land-use change and forestry (LUCF). They motivated the application of preparatory signal detection in the context of the Kyoto Protocol as a necessary measure that should have been taken prior to/in negotiating the Protocol. The authors argued that uncertainties are already monitored and are increasingly made available but that monitored emissions and uncertainties are still dealt with in isolation. A connection between emission and uncertainty estimates for the purpose of an advanced country evaluation has not yet been established. The authors developed four preparatory signal analysis techniques and applied these to the Annex B countries under the Kyoto Protocol. The frame of reference for preparatory signal detection is that Annex B countries comply with their agreed emission targets in 2008-2012. The emissions path between base year and commitment year/period is generally assumed to be a straight line, and emissions prior to the base year are not taken into consideration.
This study applies the strictest of these techniques, the combined undershooting and verification time (Und&VT) concept to advance the monitoring of the GHG emissions reported by the 27 Member States of the European Union (EU). In contrast to the earlier study, the Member States' agreed emission targets under EU burden sharing in compliance with the Kyoto Protocol are taken into account, however, still assuming that only domestic measures will be used (i.e., excluding Kyoto mechanisms). The Und&VT concept is applied in a standard mode, i.e., with reference to the Member States' agreed emission targets in 2008-2012, and in a new mode, i.e., with reference to linear path emission targets between base year and commitment year. Here, the intermediate year of reference is 2005.
To advance the reporting of the EU, uncertainty and its consequences are taken into consideration, i.e., (i) the risk that a Member State's true emissions in the commitment year/period are above its true emission limitation or reduction commitment (true emission target); and (ii) the detectability of the Member State's agreed emission target. This risk can be grasped and quantified although true emissions are unknown by definition (but not necessarily their ratios). Undershooting the agreed target, or EU-compatible but detectable target, can decrease this risk. The Member States' potential linear path undershooting opportunities as of 2005 are contrasted with their actual emission situation in that year, which is captured by the distance-to-target-path indicator (DTPI; formerly: distance-to-target indicator) previously introduced by the European Environment Agency.
In 2005, fourteen EU-27 Member States exhibit a negative DTPI and thus appear as potential sellers: Bulgaria, Czech Republic, Estonia, France, Finland, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Sweden and the United Kingdom. However, expecting that all of the EU Member States will eventually exhibit relative uncertainties in the range of 5-10% and above rather than below (excluding LUCF and Kyoto mechanisms), the Member States require considerable undershooting of their EU-compatible, but detectable, targets if one wants to keep the said risk low that the Member States' true emissions in the commitment year/period fall above their true emission targets. As of 2005, these conditions can only be met by ten (nine new and one old) Member States (ranked in terms of credibility): Latvia, Lithuania, Estonia, Bulgaria, Romania, Hungary, Slovakia, Poland, Czech Republic, and the United Kingdom; while four other Member States, Germany, Sweden, Finland and France, can only act as potential sellers with a higher risk. The other EU-27 Member States do not meet their linear path (base year-commitment year) undershooting targets as of 2005 (i.e., they overshoot their intermediate targets), or do not have Kyoto targets at all (Cyprus and Malta).
The relative uncertainty, with which countries report their emissions, matters. For instance, with relative uncertainty increasing from 5 to 10%, the linear path 2008/12 emission signal of the old EU-15 as a whole (which has jointly approved, as a Party, an 8% emission reduction under the Kyoto Protocol) switches from detectable to non-detectable, indicating that the negotiations for the Kyoto Protocol were imprudent because they did not take uncertainty and its consequences into account.
It is anticipated that the evaluation of emission signals in terms of risk and detectability will become standard practice and that these two qualifiers will be accounted for in pricing GHG emission permits
Preparatory Signal Detection for the EU-25 Member States under EU Burden Sharing/Advanced Monitoring Including Uncertainty (1990-2004)
This study follows up IIASA Interim Report IR-04-024 (Jonas et al., 2004), which addresses the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. The question probed was how well do we need to know net emissions if we want to detect a specified emission signal after a given time? The authors used the Protocol's Annex B countries as net emitters and referred to all Kyoto GHGs (CO2, CH4, N2O, HFCs, PFCs, and SF6) excluding CO2 emissions/removals due to land-use change and forestry (LUCF). They motivated the application of preparatory signal detection in the context of the Kyoto Protocol as a necessary measure that should have been taken prior to/in negotiating the Protocol. The authors argued that uncertainties are already monitored and are increasingly made available but that monitored emissions and uncertainties are still dealt with in isolation. A connection between emission and uncertainty estimates for the purpose of an advanced country evaluation has not yet been established. The authors developed four preparatory signal analysis techniques and applied these to the Annex B countries under the Kyoto Protocol. The frame of reference for preparatory signal detection is that Annex B countries comply with their agreed emission targets in 2008-2012. The emissions path between base year and commitment year/period is generally assumed to be a straight line, and emissions prior to the base year are not taken into consideration.
This study applies the strictest of these techniques, the combined undershooting and verification time (Und&VT) concept to advance the monitoring of the GHG emissions reported by the 27 Member States of the European Union (EU). In contrast to the earlier study, the Member States' agreed emission targets under EU burden sharing in compliance with the Kyoto Protocol are taken into account, however, still assuming that only domestic measures will be used (i.e., excluding Kyoto mechanisms). The Und&VT concept is applied in a standard mode, i.e., with reference to the Member States' agreed emission targets in 2008-2012, and in a new mode, i.e., with reference to linear path emission targets between base year and commitment year. Here, the intermediate year of reference is 2004.
To advance the reporting of the EU, uncertainty and its consequences are taken into consideration, i.e., (i) the risk that a Member State's true emissions in the commitment year/period are above its true emission limitation or reduction commitment (true emission target); and (ii) the detectability of the Member State's agreed emission target. This risk can be grasped and quantified although true emissions are unknown by definition (but not necessarily their ratios). Undershooting the agreed EU, or EU-compatible but detectable, target can decrease this risk. The Member States' potential linear path undershooting opportunities as of 2004 are contrasted with their actual emission situation in that year, which is captured by the distance-to-target-path indicator (DTPI; formerly: distance-to-target indicator) previously introduced by the European Environment Agency.
In 2004, eleven EU-25 Member States exhibit a negative DTPI and thus appear as potential sellers: Czech Republic, Estonia, France, Germany, Hungary, Latvia, Lithuania, Poland, Slovakia, Sweden and the United Kingdom. However, expecting that all of the EU Member States will eventually exhibit relative uncertainties in the range of 5-10% and above rather than below (excluding LUCF and Kyoto mechanisms), the Member States require considerable undershooting of their EU-compatible, but detectable, targets if one wants to keep the said risk low that the Member States' true emissions in the commitment year/period fall above their true emission targets. As of 2004, these conditions can only be met by eight (seven new and one old) Member States (ranked in terms of credibility): Latvia, Lithuania, Estonia, Poland, Hungary, Slovakia, Czech Republic, and the United Kingdom; while three old Member States, Germany, Sweden, and France, can only act as potential sellers with a higher risk. The other EU-25 Member States do not meet their linear path (base year-commitment year) emission targets as of 2004 (i.e., they overshoot their intermediate targets), or do not have Kyoto targets at all (Cyprus and Malta).
The relative uncertainty matters with which countries report their emissions. For instance, with relative uncertainty increasing from 5 to 10%, the linear path 2008/12 emission signal of the old EU-15 as a whole (which has jointly approved, as a Party, an 8% emission reduction under the Kyoto Protocol) switches from detectable to non-detectable, indicating that the negotiations for the Kyoto Protocol were imprudent because they did not take uncertainty and its consequences into account.
It is anticipated that the evaluation of emission signals in terms of risk and detectability will become standard practice and that these two qualifiers will be accounted for in pricing GHG emission permits
Preparatory Signal Detection for the EU-27 Member States Under EU Burden Sharing - Advanced Monitoring Including Uncertainty (1990-2006)
This study follows up IIASA Interim Report IR-04-024 (Jonas et al., 2004), which addresses the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. The question probed was how well do we need to know net emissions if we want to detect a specified emission signal after a given time? The authors used the Protocol's Annex B countries as net emitters and referred to all Kyoto GHGs (CO2, CH4, N2O, HFCs, PFCs, and SF6) excluding CO2 emissions/removals due to land-use change and forestry (LUCF). They motivated the application of preparatory signal detection in the context of the Kyoto Protocol as a necessary measure that should have been taken prior to/in negotiating the Protocol. The authors argued that uncertainties are already monitored and are increasingly made available but that monitored emissions and uncertainties are still dealt with in isolation. A connection between emission and uncertainty estimates for the purpose of an advanced country evaluation has not yet been established. The authors developed four preparatory signal analysis techniques and applied these to the Annex B countries under the Kyoto Protocol. The frame of reference for preparatory signal detection is that Annex B countries comply with their agreed emission targets in 2008-2012. The emissions path between base year and commitment year/period is generally assumed to be a straight line, and emissions prior to the base year are not taken into consideration. An in-depth quantitative comparison of the four, plus two additional, preparatory signal analysis techniques has been prepared by Jonas et al. (2010).
This study applies the strictest of these techniques, the combined undershooting and verification time (Und&VT) concept to advance the monitoring of the GHG emissions reported by the 27 Member States of the European Union (EU). In contrast to the study by Jonas et al. (2004), the Member States. agreed emission targets under EU burden sharing in compliance with the Kyoto Protocol are taken into account, however, still assuming that only domestic measures will be used (i.e., excluding Kyoto mechanisms). The Und&VT concept is applied in a standard mode, i.e., with reference to the Member States' agreed emission targets in 2008-2012, and in a new mode, i.e., with reference to linear path emission targets between base year and commitment year. Here, the intermediate year of reference is 2006.
To advance the reporting of the EU, uncertainty and its consequences are taken into consideration, i.e., (i) the risk that a Member State's true emissions in the commitment year/period are above its true emission limitation or reduction commitment (true emission target); and (ii) the detectability of the Member State's agreed emission target. This risk can be grasped and quantified although true emissions are unknown by definition. Undershooting the agreed target or the compatible but detectable target can decrease this risk. The Member States' undershooting options and challenges as of 2006 are contrasted with their actual emission situation in that year, which is captured by the distance-to-target-path indicator (DTPI; formerly: distance-to-target indicator) initially introduced by the European Environment Agency. This indicator measures by how much the emissions of a Member State deviate from its linear emissions path between base year and target year.
In 2006 thirteen EU-27 Member States exhibit a negative DTPI (not counting Belgium with a DTPI ~= 0) and thus appear as potential sellers: Bulgaria, the Czech Republic, Estonia, France, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Sweden and the United Kingdom. However, expecting that all of the EU Member States will eventually exhibit relative uncertainties in the range of 5.10% and above rather than below (excluding LUCF and Kyoto mechanisms), the Member States require considerable undershooting of their EU-compatible but detectable targets if one wants to keep the said risk low that the Member States' true emissions in the commitment year/period fall above their true emission targets. As of 2006, these conditions can only be met by ten (nine new and one old) Member States (ranked in terms of credibility): Estonia, Latvia, Lithuania, Bulgaria, Romania, Slovakia, Hungary, Poland, the Czech Republic and the United Kingdom; while three old Member States, Germany, Sweden and France, can only act as potential sellers with a higher risk. The other EU-27 Member States do not meet their linear path (base year--commitment year) undershooting targets as of 2005 (i.e., they overshoot their intermediate targets), or do not have Kyoto targets at all (Cyprus and Malta).
The relative uncertainty, with which countries report their emissions, matters. For instance, with relative uncertainty increasing from 5 to 10%, the 2008/12 emission reduction of the EU-15 as a whole (which has jointly approved, as a Party, an 8% emission reduction under the Kyoto Protocol) switches from detectable to non-detectable, indicating that the negotiations for the Kyoto Protocol were imprudent because they did not take uncertainty and its consequences into account.
It is anticipated that the evaluation of emission signals in terms of risk and detectability will become standard practice and that these two qualifiers will be accounted for in pricing GHG emission permits
Preparatory Signal Detection for the EU-27 Member States Under EU Burden Sharing - Advanced Monitoring Including Uncertainty (1990-2007)
This study follows up IIASA Interim Report IR-04-024 (Jonas et al., 2004), which addresses the preparatory detection of uncertain greenhouse gas (GHG) emission changes (also termed emission signals) under the Kyoto Protocol. The question probed was how well do we need to know net emissions if we want to detect a specified emission signal after a given time? The authors used the Protocol's Annex B countries as net emitters and referred to all Kyoto GHGs (CO2, CH4, N2O, HFCs, PFCs, and SF6) excluding CO2 emissions/removals due to land-use change and forestry (LUCF). They motivated the application of preparatory signal detection in the context of the Kyoto Protocol as a necessary measure that should have been taken prior to/in negotiating the Protocol. The authors argued that uncertainties are already monitored and are increasingly made available but that monitored emissions and uncertainties are still dealt with in isolation. A connection between emission and uncertainty estimates for the purpose of an advanced country evaluation has not yet been established. The authors developed four preparatory signal analysis techniques and applied these to the Annex B countries under the Kyoto Protocol. The frame of reference for preparatory signal detection is that Annex B countries comply with their agreed emission targets in 2008-2012. The emissions path between base year and commitment year/period is generally assumed to be a straight line, and emissions prior to the base year are not taken into consideration. An in-depth quantitative comparison of the four, plus two additional, preparatory signal analysis techniques has been prepared by Jonas et al. (2010).
This study applies the strictest of these techniques, the combined undershooting and verification time (Und&VT) concept to advance the monitoring of the GHG emissions reported by the 27 Member States of the European Union (EU). In contrast to the study by Jonas et al. (2004), the Member States' agreed emission targets under EU burden sharing in compliance with the Kyoto Protocol are taken into account, however, still assuming that only domestic measures will be used (i.e., excluding Kyoto mechanisms). The Und&VT concept is applied in a standard mode, i.e., with reference to the Member States' agreed emission targets in 2008-2012, and in a new mode, i.e., with reference to linear path emission targets between base year and commitment year. Here, the intermediate year of reference is 2007.
To advance the reporting of the EU, uncertainty and its consequences are taken into consideration, i.e., (i) the risk that a Member State's true emissions in the commitment year/period are above its true emission limitation or reduction commitment (true emission target); and (ii) the detectability of the Member State's agreed emission target. This risk can be grasped and quantified although true emissions are unknown by definition. Undershooting the agreed target or the compatible but detectable target can decrease this risk. The Member States' undershooting options and challenges as of 2007 are contrasted with their actual emission situation in that year, which is captured by the distance-to-target-path indicator (DTPI; formerly: distance-to-target indicator) initially introduced by the European Environment Agency. This indicator measures by how much the emissions of a Member State deviate from its linear emissions path between base year and target year.
In 2007, fourteen EU-27 Member States exhibit a negative DTPI and thus appear as potential sellers: Belgium, Bulgaria, Czech Republic, Estonia, France, Germany, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia, Sweden, and the United Kingdom. However, expecting that all of the EU Member States will eventually exhibit relative uncertainties in the range of 5-10% and above rather than below (excluding LUCF and Kyoto mechanisms), the Member States require considerable undershooting of their EU-compatible but detectable targets if one wants to keep the said risk low that the Member States' true emissions in the commitment year/period fall above their true emission targets. As of 2007, these conditions can only be met by ten (nine new and one old) Member States (ranked in terms of credibility): Latvia, Lithuania, Estonia, Romania, Bulgaria, Slovakia, Hungary, Poland, the Czech Republic and the United Kingdom; while four Member States, Germany, Belgium, Sweden and France, can only act as potential sellers with a higher risk. The other EU-27 Member States do not meet their linear path (base year-commitment year) undershooting targets as of 2007 (i.e., they overshoot their intermediate targets), or do not have Kyoto targets at all (Cyprus and Malta).
The relative uncertainty, with which countries report their emissions, matters. For instance, with relative uncertainty increasing from 5 to 10%, the 2008/12 emission reduction of the EU-15 as a whole (which has jointly approved, as a Party, an 8% emission reduction under the Kyoto Protocol) switches from detectable to non-detectable, indicating that the negotiations for the Kyoto Protocol were imprudent because they did not take uncertainty and its consequences into account.
It is anticipated that the evaluation of emission signals in terms of risk and detectability will become standard practice and that these two qualifiers will be accounted for in pricing GHG emission permits
Cystoscopic removal of an intravesical gossypiboma mimicking a bladder mass: a case report
<p>Abstract</p> <p>Background</p> <p>Intravesical retained surgical sponges are very rare and only a few cases have been removed by minimally invasive techniques.</p> <p>Case presentation</p> <p>We report a case of an intravesical gossypiboma in a 71-year-old man from western Nepal, who presented with urinary retention and persistent lower urinary tract symptoms one year after open cystolithotomy. He was diagnosed with an intravesical mass using ultrasonography. The retained surgical sponge was found during cystoscopy and removed through endoscopy.</p> <p>Conclusion</p> <p>Intravesical gossypibomas are rare and can mimic a bladder mass. This is one of the few reported cases of cystoscopic removal.</p
Rapid gains in yield and adoption of new maize varieties for complex hillside environments through farmer participation. II. Scaling-up the adoption through community-based seed production (CBSP)
Participatory varietal selection (PVS) led to the identification of Population-22 and its later release as Manakamana-3. Subsequently further mother–baby trials tested five unreleased open-pollinated varieties (OPVs), ZM-621, Shitala, Population-45, Hill Pool White, and Hill Pool Yellow to compare them with Manakamana-3. Farmers again preferred Manakamana-3 as well as ZM-621 for their stable, higher grain yield, and for other traits such as stay-green, non-lodging, large white grains, and tolerance to foliar diseases. However, Manakamana- 3 and ZM-621 both had late maturity, open husks and dented grain. Both were tested with farmers on-farm coordinated farmers field trials (CFFTs) and had not been identified as this was more contractual type of participatory research. Individual traits were measured but overall farmers’ preferences were not elicited. In the more collaborative participation of the mother– baby trials the overall preference was determined and farmers traded-off the late maturity and dented grains of Manakamana-3 and ZM-621 against other favorable traits. Depending on location, these genotypes yielded 15–45% more grain than the local varieties in the mother–baby trials. These results led to the release of ZM-621 as Deuti in 2006. Farmers had adopted Manakamana-3 (released in 2002) and ZM-621 (Deuti) as a direct result of PVS trials and increased area under them year after year. Farmers awareness of the varieties has increased and seeds of these varieties are under community-based seed production (CBSP). Involving farmers through a collaborative mode of participation in varietal selection overcame bottlenecks to finding new varieties that had occurred with more contractual on-farm research
A comparative analysis of machine learning algorithms for detecting COVID-19 using lung X-ray images
Machine intelligence has the potential to play a significant role in diagnosing, managing, and guiding the treatment of disease, which supports the rising demands on healthcare to provide rapid and accurate interpretation of clinical data. The global pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus (SARSCoV-2) exposed a need for rapid clinical data interpretation in response to an unprecedented burden on the healthcare system. A new healthcare challenge has arisen – post-COVID syndrome or ‘long COVID’. Symptoms of the post-COVID syndrome can persist for months following infection with SARS-CoV-2, often characterised by fatigue, breathlessness, dizziness, and pain. Despite this additional healthcare burden, no tests can diagnose, monitor, or determine the efficacy of treatments/interventions to support recovery. In this paper, an array of machine-learning algorithms is trained to evaluate and detect COVID-19-associated changes to lung tissue from X-ray images. X-ray images are classified from open sources into three categories: COVID-19 patients, patients with pneumonia, and unaffected otherwise healthy individuals using existing Machine Learning (ML) and pre-trained deep learning models. Prioritising models with the fewest false positives and false negatives assessed the performance of different models in detecting COVID-19-associated lung tissue. In addition, image pre-processing, data augmentation, and hyperparameter tuning are used to achieve the best accuracy in the models. Different ML models, including K Nearest Neighbour (KNN), and decision trees (DT), as well as transfer learning models such as Convolutional Neural Network (CNN), Visual Geometry Group (VGG-16, VGG-19), ResNet50, DenseNet201, Xception, and InceptionV3, were tested to evaluate the performance of these models for X-ray images classification. The comparative analysis indicates that VGG-19 with augmentation performed best among the ten algorithms with a training accuracy of 99%, testing accuracy of 98%, and precision of 90% for COVID-19, 90% for normal, and 100% for pneumonia. This higher accuracy for detecting COVID-19-associated lung changes on X-ray may be further developed to stratify patients suffering from post-COVID syndrome. This may enable future intervention studies to determine the efficacy of treatments or better track patients’ prognoses to be optimised
Measurement of Atmospheric Neutrino Oscillations with the ANTARES Neutrino Telescope
The data taken with the ANTARES neutrino telescope from 2007 to 2010, a total
live time of 863 days, are used to measure the oscillation parameters of
atmospheric neutrinos. Muon tracks are reconstructed with energies as low as 20
GeV. Neutrino oscillations will cause a suppression of vertical upgoing muon
neutrinos of such energies crossing the Earth. The parameters determining the
oscillation of atmospheric neutrinos are extracted by fitting the event rate as
a function of the ratio of the estimated neutrino energy and reconstructed
flight path through the Earth. Measurement contours of the oscillation
parameters in a two-flavour approximation are derived. Assuming maximum mixing,
a mass difference of eV is
obtained, in good agreement with the world average value.Comment: 9 pages, 5 figure
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