ROMANIA IN EU CONTEXT. COMPETITIVENESS AND KNOWLEDGE-BASED ECONOMY

The paper analyses Romania’s competitiveness and knowledge-based economyin an EU comparative context for the 2006-2007 period. The main compared pillar-indices are the following: global competitiveness index;higher education and training; technological readiness; business sophistication; innovation.Each pillar index is disaggregated into several relevant sub indices. Comparisons are madebetween Romania and EU-25, EU-10 (new member states since 2004), Bulgaria and Turkeyon the basis of positions and scores of each country or group of countries, within a totalframework of 131 countries. The size of Romania’s digital divide vis-à-vis EU-25 can beused as a tool for national priority setting and better policies regarding catching up andconvergence processes in digital economy.competitiveness; knowledge-based society; national and international value chains;catching-up; convergence; digital divide; brain drain; knowledge creation, absorption and diffusion.

Delivering reproductive health services through non-state providers in Pakistan: Understanding the value for money of different approaches

Sophie Witter - orcid: 0000-0002-7656-6188 https://orcid.org/0000-0002-7656-6188Background - Delivering Reproductive Health Results(DRHR) programme used social franchising (SF) and social marketing (SM) approaches to increase the supply of high quality family planning services in underserved areas of Pakistan. We assessed the costs, cost-efficiency and cost-effectiveness of DRHR to understand the value for money of these approaches.Methods - Financial and economic programme costs were calculated. Costs to individual users were captured in a pre-post survey. The cost per couple years of protection (CYP) and cost per new user were estimated as indicators of cost efficiency. For the cost-effectiveness analysis we estimated the cost per clinical outcome averted and the cost per disability-adjusted life year (DALY) averted.Results - Approximately £20 million were spent through the DRHR programme between July 2012 and September 2015 on commodities and services representing nearly four million CYPs. Based on programme data, the cumulative cost-efficiency of the entire DRHR programme was £4.8 per CYP. DRHR activities would avert one DALY at the cost of £20. Financial access indicators generally improved in programme areas, but the magnitude of progress varies across indicators.Conclusions - The SF and SM approaches adopted in DRHR appear to be cost effective relative to comparable reproductive health programmes. This paper adds to the limited evidence on the cost-effectiveness of different models of reproductive health care provision in low- and middle-income settings. Further studies are needed to nuance the understanding of the determinants of impact and value for money of SF and SM.This study was funded by UKaid from the UK government. However, the views expressed do not necessarily reflect the UK government’s official policies.3 [33]pubpu

Automatic eduction and statistical analysis of coherent structures in the wall region of a confine plane

This paper describes a vortex detection algorithm used to expose and statistically characterize the coherent flow patterns observable in the velocity vector fields measured by Particle Image Velocimetry (PIV) in the impingement region of air curtains. The philosophy and the architecture of this algorithm are presented. Its strengths and weaknesses are discussed. The results of a parametrical analysis performed to assess the variability of the response of our algorithm to the 3 user-specified parameters in our eduction scheme are reviewed. The technique is illustrated in the case of a plane turbulent impinging twin-jet with an opening ratio of 10. The corresponding jet Reynolds number, based on the initial mean flow velocity U0 and the jet width e, is 14000. The results of a statistical analysis of the size, shape, spatial distribution and energetic content of the coherent eddy structures detected in the impingement region of this test flow are provided. Although many questions remain open, new insights into the way these structures might form, organize and evolve are given. Relevant results provide an original picture of the plane turbulent impinging jet

Evaluating maize genotype performance under low nitrogen conditions using RGB UAV phenotyping techniques

Maize is the most cultivated cereal in Africa in terms of land area and production, but low soil nitrogen availability often constrains yields. Developing new maize varieties with high and reliable yields using traditional crop breeding techniques in field conditions can be slow and costly. Remote sensing has become an important tool in the modernization of field-based high-throughput plant phenotyping (HTPP), providing faster gains towards the improvement of yield potential and adaptation to abiotic and biotic limiting conditions. We evaluated the performance of a set of remote sensing indices derived from red–green–blue (RGB) images along with field-based multispectral normalized difference vegetation index (NDVI) and leaf chlorophyll content (SPAD values) as phenotypic traits for assessing maize performance under managed low-nitrogen conditions. HTPP measurements were conducted from the ground and from an unmanned aerial vehicle (UAV). For the ground-level RGB indices, the strongest correlations to yield were observed with hue, greener green area (GGA), and a newly developed RGB HTPP index, NDLab (normalized difference Commission Internationale de I´Edairage (CIE)Lab index), while GGA and crop senescence index (CSI) correlated better with grain yield from the UAV. Regarding ground sensors, SPAD exhibited the closest correlation with grain yield, notably increasing in its correlation when measured in the vegetative stage. Additionally, we evaluated how different HTPP indices contributed to the explanation of yield in combination with agronomic data, such as anthesis silking interval (ASI), anthesis date (AD), and plant height (PH). Multivariate regression models, including RGB indices (R2 > 0.60), outperformed other models using only agronomic parameters or field sensors (R2 > 0.50), reinforcing RGB HTPP’s potential to improve yield assessments. Finally, we compared the low-N results to the same panel of 64 maize genotypes grown under optimal conditions, noting that only 11% of the total genotypes appeared in the highest yield producing quartile for both trials. Furthermore, we calculated the grain yield loss index (GYLI) for each genotype, which showed a large range of variability, suggesting that low-N performance is not necessarily exclusive of high productivity in optimal conditions.This research and APC was funded by Bill & Melinda Gates Foundation and USAID Stress Tolerant Maize for Africa program, grant number [OPP1134248], and the MAIZE CGIAR research program. The CGIAR Research Program MAIZE receives W1&W2 support from the Governments of Australia, Belgium, Canada, China, France, India, Japan, Korea, Mexico, Netherlands, New Zealand, Norway, Sweden, Switzerland, U.K., U.S., and the World Bank

Evaluating Maize Genotype Performance under Low Nitrogen Conditions Using RGB UAV Phenotyping Techniques

Maize is the most cultivated cereal in Africa in terms of land area and production, but low soil nitrogen availability often constrains yields. Developing new maize varieties with high and reliable yields using traditional crop breeding techniques in field conditions can be slow and costly. Remote sensing has become an important tool in the modernization of field-based high-throughput plant phenotyping (HTPP), providing faster gains towards the improvement of yield potential and adaptation to abiotic and biotic limiting conditions. We evaluated the performance of a set of remote sensing indices derived from red-green-blue (RGB) images along with field-based multispectral normalized difference vegetation index (NDVI) and leaf chlorophyll content (SPAD values) as phenotypic traits for assessing maize performance under managed low-nitrogen conditions. HTPP measurements were conducted from the ground and from an unmanned aerial vehicle (UAV). For the ground-level RGB indices, the strongest correlations to yield were observed with hue, greener green area (GGA), and a newly developed RGB HTPP index, NDLab (normalized difference Commission Internationale de I´Edairage (CIE)Lab index), while GGA and crop senescence index (CSI) correlated better with grain yield from the UAV. Regarding ground sensors, SPAD exhibited the closest correlation with grain yield, notably increasing in its correlation when measured in the vegetative stage. Additionally, we evaluated how different HTPP indices contributed to the explanation of yield in combination with agronomic data, such as anthesis silking interval (ASI), anthesis date (AD), and plant height (PH). Multivariate regression models, including RGB indices (R2 > 0.60), outperformed other models using only agronomic parameters or field sensors (R2 > 0.50), reinforcing RGB HTPP's potential to improve yield assessments. Finally, we compared the low-N results to the same panel of 64 maize genotypes grown under optimal conditions, noting that only 11% of the total genotypes appeared in the highest yield producing quartile for both trials. Furthermore, we calculated the grain yield loss index (GYLI) for each genotype, which showed a large range of variability, suggesting that low-N performance is not necessarily exclusive of high productivity in optimal conditions

Leaf versus whole-canopy remote sensing methodologies for crop monitoring under conservation agriculture: a case of study with maize in Zimbabwe

Enhancing nitrogen fertilization efficiency for improving yield is a major challenge for smallholder farming systems. Rapid and cost-effective methodologies with the capability to assess the effects of fertilization are required to facilitate smallholder farm management. This study compares maize leaf and canopy-based approaches for assessing N fertilization performance under different tillage, residue coverage and top-dressing conditions in Zimbabwe. Among the measurements made on individual leaves, chlorophyll readings were the best indicators for both N content in leaves (R < 0.700) and grain yield (GY) (R < 0.800). Canopy indices reported even higher correlation coefficients when assessing GY, especially those based on the measurements of the vegetation density as the green area indices (R < 0.850). Canopy measurements from both ground and aerial platforms performed very similar, but indices assessed from the UAV performed best in capturing the most relevant information from the whole plot and correlations with GY and leaf N content were slightly higher. Leaf-based measurements demonstrated utility in monitoring N leaf content, though canopy measurements outperformed the leaf readings in assessing GY parameters, while providing the additional value derived from the affordability and easiness of using a pheno-pole system or the high-throughput capacities of the UAVs

Comparative performance of ground vs. aerially assessed RGB and multispectral indices for early-growth evaluation of maize performance under phosphorus fertilization

Low soil fertility is one of the factors most limiting agricultural production, with phosphorus deficiency being among the main factors, particularly in developing countries. To deal with such environmental constraints, remote sensing measurements can be used to rapidly assess crop performance and to phenotype a large number of plots in a rapid and cost-effective way. We evaluated the performance of a set of remote sensing indices derived from Red-Green-Blue (RGB) images and multispectral (visible and infrared) data as phenotypic traits and crop monitoring tools for early assessment of maize performance under phosphorus fertilization. Thus, a set of 26 maize hybrids grown under field conditions in Zimbabwe was assayed under contrasting phosphorus fertilization conditions. Remote sensing measurements were conducted in seedlings at two different levels: at the ground and from an aerial platform. Within a particular phosphorus level, some of the RGB indices strongly correlated with grain yield. In general, RGB indices assessed at both ground and aerial levels correlated in a comparable way with grain yield except for indices a* and u*, which correlated better when assessed at the aerial level than at ground level and Greener Area (GGA) which had the opposite correlation. The Normalized Difference Vegetation Index (NDVI) evaluated at ground level with an active sensor also correlated better with grain yield than the NDVI derived from the multispectral camera mounted in the aerial platform. Other multispectral indices like the Soil Adjusted Vegetation Index (SAVI) performed very similarly to NDVI assessed at the aerial level but overall, they correlated in a weaker manner with grain yield than the best RGB indices. This study clearly illustrates the advantage of RGB-derived indices over the more costly and time-consuming multispectral indices. Moreover, the indices best correlated with GY were in general those best correlated with leaf phosphorous content. However, these correlations were clearly weaker than against grain yield and only under low phosphorous conditions. This work reinforces the effectiveness of canopy remote sensing for plant phenotyping and crop management of maize under different phosphorus nutrient conditions and suggests that the RGB indices are the best option

Quality assurance process within the RAdiosurgery for VENtricular TAchycardia (RAVENTA) trial for the fusion of electroanatomical mapping and radiotherapy planning imaging data in cardiac radioablation

A novel quality assurance process for electroanatomical mapping (EAM)-to-radiotherapy planning imaging (RTPI) target transport was assessed within the multi-center multi-platform framework of the RAdiosurgery for VENtricular TAchycardia (RAVENTA) trial. A stand-alone software (CARDIO-RT) was developed to enable platform independent registration of EAM and RTPI of the left ventricle (LV), based on pre-generated radiotherapy contours (RTC). LV-RTC were automatically segmented into the American-Heart-Association 17-segment-model and a manual 3D-3D method based on EAM 3D-geometry data and a semi-automated 2D-3D method based on EAM screenshot projections were developed. The quality of substrate transfer was evaluated in five clinical cases and the structural analyses showed substantial differences between manual target transfer and target transport using CARDIO-RT

Safety and efficacy of everolimus-eluting bioabsorbable polymer-coated stent in patients with long coronary lesions: the EVOLVE 48 study

Objectives: The EVOLVE 48 study evaluated the safety and effectiveness of the SYNERGY 48 mm stent for the treatment of long lesions. Background: Clinical evidence supporting the use of very long stents during percutaneous coronary intervention (PCI) is limited. The bioabsorbable polymer SYNERGY stent has shown good long-term data in a broad population of patients undergoing PCI. Methods: Patients with lesion length &gt;34- ≤44 mm and reference vessel diameter (RVD) ≥2.5- ≤ 4.0 mm were enrolled in this prospective, multicenter, single-arm study. The primary endpoint was 12-month target lesion failure (TLF; composite of target lesion revascularization [TLR], target-vessel myocardial infarction [TV-MI], or cardiac death) compared to a prespecified performance goal (PG). Results: A total of 100 patients with mean lesion length of 35.34 ± 7.15 mm (26 patients with lesion length &gt; 40 mm) and mean RVD 2.72 ± 0.44 mm were enrolled. Moderate to severe calcification was present in 30% of the patients and 89% had pre-TIMI flow grade 3. The rates of technical and clinical procedural success were 100%. One-year TLF was observed in 4.1% patients compared to a prespecified PG of 19.5% (95% upper confidence bound = 9.1%; p &lt; 0.0001). Cardiac death and TLR were each observed in one patient, and TV-MI in two patients treated with SYNERGY 48 mm stent. Between the 1-2-year timeframe, TV-MI occurred in one additional patient. None of the patients experienced a definite or probable stent thrombosis through 2 years. Conclusions: PCI of long coronary lesions with the 48 mm SYNERGY stent demonstrated good procedural and clinical outcomes through 2 years, supporting its clinical safety and efficacy

Development of an online p38α mitogen-activated protein kinase binding assay and integration of LC–HR-MS

A high-resolution screening method was developed for the p38α mitogen-activated protein kinase to detect and identify small-molecule binders. Its central role in inflammatory diseases makes this enzyme a very important drug target. The setup integrates separation by high-performance liquid chromatography with two parallel detection techniques. High-resolution mass spectrometry gives structural information to identify small molecules while an online enzyme binding detection method provides data on p38α binding. The separation step allows the individual assessment of compounds in a mixture and links affinity and structure information via the retention time. Enzyme binding detection was achieved with a competitive binding assay based on fluorescence enhancement which has a simple principle, is inexpensive, and is easy to interpret. The concentrations of p38α and the fluorescence tracer SK&F86002 were optimized as well as incubation temperature, formic acid content of the LC eluents, and the material of the incubation tubing. The latter notably improved the screening of highly lipophilic compounds. For optimization and validation purposes, the known kinase inhibitors BIRB796, TAK715, and MAPKI1 were used among others. The result is a high-quality assay with Z′ factors around 0.8, which is suitable for semi-quantitative affinity measurements and applicable to various binding modes. Furthermore, the integrated approach gives affinity data on individual compounds instead of averaged ones for mixtures