Environmental assessment tools for the evaluation and improvement of European livestock production systems

Different types of assessment tools have been developed in Europe with the purpose of determining the environmental impact of various livestock production systems at farm level. The assessment tools differ in terms of which environmental objectives are included and how indicators are constructed and interpreted. The paper compares typical tools for environmental assessment of livestock production systems, and recommends selected indicators suitable for benchmarking. The assessment tools used very different types of indicators ranging from descriptions of farm management and quantification of input to estimates of emissions of, e.g., nitrate and ammonia. The indicators should be useful in a benchmarking process where farmers may improve their practices through learning from farms with better agri-environmental performance. An example of this is given using data on P-surplus on pig farms. Some indicators used the area of the farm as the basis of the indicator — e.g. nitrogen surplus per hectare — while others were expressed per unit produced, e.g. emission of greenhouse gasses per kilogram milk. The paper demonstrates that a comparison of organic vs. conventional milk production and comparison of three pig production systems give different results, depending on the basis of the indicators (i.e. per hectare or per kilogram product). Indicators linked to environmental objectives with a local or regional geographical target should be area-based — while indicators with a global focus should be product-based. It is argued that the choice of indicators should be linked with the definition of the system boundaries, in the sense that area-based indicators should include emissions on the farm only, whereas product-based indicators should preferably include emissions from production of farm inputs, as well as the inputs on the actual farm. The paper ends with recommendations for choice of agri-environmental indicators taking into account the geographical scale, system boundary and method of interpretation

Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data

To evaluate whether the contrast-to-noise ratio (CNR) of an iodinated contrast agent in virtual monoenergetic images (VMI) from the first clinical photon-counting detector (PCD) CT scanner is superior to VMI CNR from a dual-source dual-energy CT scanner with energy-integrating detectors (EID), two anthropomorphic phantoms in three different sizes (thorax and abdomen, QRM GmbH), in combination with a custom-built insert containing cavities filled with water, and water with 15 mg iodine/mL, were scanned on an EID-based scanner (Siemens SOMATOM Force) and on a PCD-based scanner (Siemens, NAEOTOM Alpha). VMI (range 40–100 keV) were reconstructed without an iterative reconstruction (IR) technique and with an IR strength of 60% for the EID technique (ADMIRE) and closest matching IR strengths of 50% and 75% for the PCD technique (QIR). CNR was defined as the difference in mean CT numbers of water, and water with iodine, divided by the root mean square value of the measured noise in water, and water with iodine. A two-sample t-test was performed to evaluate differences in CNR between images. A p-value &lt; 0.05 was considered statistically significant. For VMI without IR and below 60 keV, the CNR of the PCD-based images at 120 and 90 kVp was up to 55% and 75% higher than the CNR of the EID-based images, respectively (p &lt; 0.05). For VMI above 60 keV, CNRs of PCD-based images at both 120 and 90 kVp were up to 20% lower than the CNRs of EID-based images. Similar or improved performance of PCD-based images in comparison with EID-based images were observed for VMIs reconstructed with IR techniques. In conclusion, with PCD-CT, iodine CNR on low energy VMI (&lt;60 keV) is better than with EID-CT.</p

In situelectromagnetic field diagnostics with an electron plasma in a Penning–Malmberg trap

We demonstrate a novel detection method for the cyclotron resonance frequency of an electron plasma in a Penning–Malmberg trap. With this technique, the electron plasma is used as an in situ diagnostic tool for the measurement of the static magnetic field and the microwave electric field in the trap. The cyclotron motion of the electron plasma is excited by microwave radiation and the temperature change of the plasma is measured non-destructively by monitoring the plasma’s quadrupole mode frequency. The spatially resolved microwave electric field strength can be inferred from the plasma temperature change and the magnetic field is found through the cyclotron resonance frequency. These measurements were used extensively in the recently reported demonstration of resonant quantum interactions with antihydrogen

An experimental limit on the charge of antihydrogen

The properties of antihydrogen are expected to be identical to those of hydrogen, and any differences would constitute a profound challenge to the fundamental theories of physics. The most commonly discussed antiatom-based tests of these theories are searches for antihydrogen-hydrogen spectral differences (tests of CPT (charge-parity-time) invariance) or gravitational differences (tests of the weak equivalence principle). Here we, the ALPHA Collaboration, report a different and somewhat unusual test of CPT and of quantum anomaly cancellation. A retrospective analysis of the influence of electric fields on antihydrogen atoms released from the ALPHA trap finds a mean axial deflection of 4.1±3.4 mm for an average axial electric field of 0.51 V mm−1. Combined with extensive numerical modelling, this measurement leads to a bound on the charge Qe of antihydrogen of Q=(−1.3±1.1±0.4) × 10^−8. Here, e is the unit charge, and the errors are from statistics and systematic effects

Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks:a robotic simulating study on influential factors

Abstract Background Motion artifacts affect the images of coronary calcified plaques. This study utilized convolutional neural networks (CNNs) to classify the motion-contaminated images of moving coronary calcified plaques and to determine the influential factors for the classification performance. Methods Two artificial coronary arteries containing four artificial plaques of different densities were placed on a robotic arm in an anthropomorphic thorax phantom. Each artery moved linearly at velocities ranging from 0 to 60 mm/s. CT examinations were performed with four state-of-the-art CT systems. All images were reconstructed with filtered back projection and at least three levels of iterative reconstruction. Each examination was performed at 100%, 80% and 40% radiation dose. Three deep CNN architectures were used for training the classification models. A five-fold cross-validation procedure was applied to validate the models. Results The accuracy of the CNN classification was 90.2 ± 3.1%, 90.6 ± 3.5%, and 90.1 ± 3.2% for the artificial plaques using Inception v3, ResNet101 and DenseNet201 CNN architectures, respectively. In the multivariate analysis, higher density and increasing velocity were significantly associated with higher classification accuracy (all P  0.05). Conclusions The CNN achieved a high accuracy of 90% when classifying the motion-contaminated images into the actual category, regardless of different vendors, velocities, radiation doses, and reconstruction algorithms, which indicates the potential value of using a CNN to correct calcium scores

Understanding and optimizing species mixtures using functional–structural plant modelling

Plant species mixtures improve productivity over monocultures by exploiting species complementarities for resource capture in time and space. Complementarity results in part from competition avoidance responses that maximize resource capture and growth of individual plants. Individual organs accommodate to local resource levels, e.g. with regard to nitrogen content and photosynthetic capacity or by size (e.g. shade avoidance). As a result, the resource acquisition in time and space is improved and performance of the community as a whole is increased. Modelling is needed to unravel the primary drivers and subsequent dynamics of complementary growth responses in mixtures. Here, we advocate using functional–structural plant (FSP) modelling to analyse the functioning of plant mixtures. In FSP modelling, crop performance is a result of the behaviour of the individual plants interacting through competitive and complementary resource acquisition. FSP models can integrate the interactions between structural and physiological plant responses to the local resource availability and strength of competition, which drive resource capture and growth of individuals in species mixtures. FSP models have the potential to accelerate mixed-species plant research, and thus support the development of knowledge that is needed to promote the use of mixtures towards sustainably increasing crop yields at acceptable input levels

Coronary calcium scores on dual-source photon-counting computed tomography:an adapted Agatston methodology aimed at radiation dose reduction

OBJECTIVES: The aim of this study was to determine mono-energetic (monoE) level-specific photon-counting CT (PCCT) Agatston thresholds, to yield monoE level independent Agatston scores validated with a dynamic cardiac phantom. Also, we examined the potential of dose reduction for PCCT coronary artery calcium (CAC) studies, when reconstructed at low monoE levels. METHODS: Theoretical CAC monoE thresholds were calculated with data from the National Institute of Standards and Technology (NIST) database. Artificial CAC with three densities were moved in an anthropomorphic thorax phantom at 0 and 60-75 bpm, and scanned at full and 50% dose on a first-generation dual-source PCCT. For all densities, Agatston scores and maximum CT numbers were determined. Agatston scores were compared with the reference at full dose and 70 keV monoE level; deviations (95% confidence interval) < 10% were deemed to be clinically not-relevant. RESULTS: Averaged over all monoE levels, measured CT numbers deviated from theoretical CT numbers by 6%, 13%, and - 4% for low-, medium-, and high-density CAC, respectively. At 50% reduced dose and 60-75 bpm, Agatston score deviations were non-relevant for 60 to 100 keV and 60 to 120 keV for medium- and high-density CAC, respectively. CONCLUSION: MonoE level-specific Agatston score thresholds resulted in similar scores as in standard reconstructions at 70 keV. PCCT allows for a potential dose reduction of 50% for CAC scoring using low monoE reconstructions for medium- and high-density CAC. KEY POINTS: • Mono-energy level-specific Agatston thresholds allow for reproducible coronary artery calcium quantification on mono-energetic images. • Increased calcium contrast-to-noise ratio at reduced mono-energy levels allows for coronary artery calcium quantification at 50% reduced radiation dose for medium- and high-density calcifications

Reproducibility of coronary artery calcium quantification on dual-source CT and dual-source photon-counting CT:a dynamic phantom study

To systematically compare coronary artery calcium (CAC) quantification between conventional computed tomography (CT) and photon-counting CT (PCCT) at different virtual monoenergetic (monoE) levels for different heart rates. A dynamic (heart rates of 0,  75 bpm) anthropomorphic phantom with three calcification densities was scanned using routine clinical CAC protocols with CT and PCCT. In addition to the standard clinical protocol of 70 keV, PCCT images were reconstructed at monoE levels of 72, 74, and 76 keV. CAC was quantified using Agatston, volume, and mass scores. Agatston scores 95% confidence intervals (CI) were calculated and compared between PCCT and CT. Volume and mass scores were compared with physical quantities. For all CAC densities, routine clinical protocol Agatston scores of static CAC were higher for PCCT compared to CT. At < 60 bpm, Agatston scores at 74 and 76 keV reconstructions were reproducible (overlapping CI) for PCCT and CT. Increased heart rates yielded different Agatston scores for PCCT in comparison with CT, for all monoE levels. Low density CAC volume scores showed the largest deviation from physical volume, with mean deviations of 59% and 77% for CT and PCCT, respectively. Overall, mass scores underestimated physical mass by 10%, 38%, and 59% for low, medium, and high density CAC, respectively. PCCT allows for reproducible Agatston scores for dynamic CAC (< 60 bpm) when reconstructed at monoE levels of 74 or 76 keV, regardless of CAC density. Deviations from physical volume and mass were, in general, large for both CT and PCCT

Dose reduction for CT coronary calcium scoring with a calcium-aware image reconstruction technique: a phantom study

Objective: To assess the dose reduction potential of a calcium-aware reconstruction technique, which aims at tube voltage-independent computed tomography (CT) numbers for calcium. Methods and materials: A cardiothoracic phantom, mimicking three different patient sizes, was scanned with two calcium inserts (named D100 and CCI), containing calcifications varying in size and density. Tube voltage was varied both manually (range 70–150 and Sn100 kVp) and automatically. Tube current was automatically adapted to maintain reference image quality defined at 120 kVp. Data was reconstructed with the standard reconstruction technique (kernel Qr36) and the calcium-aware reconstruction technique (kernel Sa36). We assessed the radiation dose reduction potential (volumetric CT dose index values (CTDIvol)), noise (standard deviation (SD)), mean CT number (HU) of each calcification, and Agatston scores for varying kVp. Results were compared with the reference acquired at 120 kVp and reconstructed with Qr36. Results: Automatic selection of the optimal tube voltage resulted in a CTDIvol reduction of 22%, 15%, and 12% compared with the reference for the small, medium, and large phantom, respectively. CT numbers differed up to 64% for the standard reconstruction and 11% for the calcium-aware reconstruction. Similarly, Agatston scores deviated up to 40% and 8% for the standard and calcium-aware reconstruction technique, respectively. Conclusion: CT numbers remained consistent with comparable calcium scores when the calcium-aware image reconstruction technique was applied with varying tube voltage. Less consistency was observed in small calcifications with low density. Automatic reduction of tube voltage resulted in a dose reduction of up to 22%. Key Points: •