Increasing Field Size Research Articles

Assessment of peripheral dose as a function of distance and depth from cobalt-60 beam in water phantom using TLD-100

BackgroundInnovations in cancer treatment have contributed to the improved survival rate of cancer patients. The cancer survival rates have been growing and nearly two third of those survivors have been exposed to clinical radiation during their treatment. The study of long-term radiation effects, especially secondary cancer induction, has become increasingly important. An accurate assessment of out-of-field/peripheral dose (PDs) is necessary to estimate the risk of second cancer after radiotherapy and the damage to the organs at risk surrounding the planning target volume. This study was designed to measure the PDs as a function of dose, distances, and depths from Telecobalt-60 (Co-60) beam in water phantom using thermoluminescent dosimeter-100 (TLD-100).MethodsThe PDs were measured for Co-60 beam at specified depths of 0 cm (surface), 5 cm, 10 cm, and 15 cm outside the radiation beam at distances of 5, 10, and 13 cm away from the radiation field edge using TLD-100 (G1 cards) as detectors. These calibrated cards were placed on the acrylic disc in circular tracks. The radiation dose of 2000 mGy of Co-60 beam was applied inside 10 × 10 cm2 field size at constant source to surface distance (SSD) of 80 cm.ResultsThe results showed maximum and minimum PDs at surface and 5 cm depth respectively at all distances from the radiation field edge. Dose distributions out of the field edge with respect to distance were isotropic. The decrease in PDs at 5 cm depth was due to dominant forward scattering of Co-60 gamma rays. The increase in PDs beyond 5 cm depth was due to increase in the irradiated volume, increase in penumbra, increase in source to axis distance (SAD), and increase in field size due to inverse square factor.ConclusionIt is concluded that the PDs depends upon depth and distance from the radiation field edge. All the measurements show PDs in the homogenous medium (water); therefore, it estimates absorbed dose to the organ at risk (OAR) adjacent to cancer tissues/planning target volume (PTV). It is suggested that PDs can be minimized by using the SAD technique, as this technique controls sources of scattered radiation like inverse square factor and effect of penumbra up-to some extent.

Skin dose investigations on a 0.5 T parallel rotating biplanar linac-MR using Monte Carlo simulations and measurements.

The Alberta rotating biplanar linac-MR has a 0.5 T magnetic field parallel to the beamline. When developing a new linac-MR system, interactions of charged particles with the magnetic field necessitate careful consideration of skin dose and tissue interface effects. To investigate the effect of the magnetic field on skin dose using measurements and Monte Carlo (MC) simulations. We develop an MC model of our linac-MR, which we validate by comparison with ion chamber measurements in a water tank. Additionally, MC simulation results are compared with radiochromic film surface dose measurements on solid water. Variations in surface dose as a function of field size are measured using a parallel plate ion chamber in solid water. Using an anthropomorphic computational phantom with a 2mm-thick skin layer, we investigate dose distributions resulting from three beam arrangements. Magnetic field on and off scenarios are considered for all measurements and simulations. For a 20×20cm2 field size, (the minimum dose to the hottest contiguous 0.2 cc volume) for the top 2mm of a simple water phantom is 72% when the magnetic field is on, compared to 34% with magnetic field off (values are normalized to the central axis dose maximum). Parallel plate ion chamber measurements demonstrate that the relative increase in surface dose due to the magnetic field decreases with increasing field size. For the anthropomorphic phantom, (minimum skin dose in the hottest 1×1×1 cm3 cube) shows relative increases of 20%-28% when the magnetic field is on compared to when it is off. With magnetic field off, skin is 71%, 56%, and 21% for medial-lateral tangents, anterior-posterior beams, and a five-field arrangement, respectively. For magnetic field on, the corresponding skin values are 91%, 67%, and 25%. Using a validated MC model of our linac-MR, surface doses are calculated in various scenarios. MC-calculated skin dose varies depending on field sizes, obliquity, and the number of beams. In general, the parallel linac-MR arrangement results in skin dose enhancement due to charged particles spiraling along magnetic field lines, which impedes lateral motion away from the central axis. Nonetheless, considering the results presented herein, treatment plans can be designed to minimize skin dose by, for example, avoiding oblique beams and using a larger number of fields.

Woody semi‐natural habitats modulate the effects of field size and functional crop diversity on farmland birds

Abstract Agricultural intensification has simplified landscape composition and configuration, which has led to biodiversity declines. Increasing landscape‐wide crop heterogeneity can promote farmland biodiversity. However, knowledge is still lacking on how the effects of configurational and compositional crop heterogeneity (i.e. field size and crop diversity) are modulated by the amount of semi‐natural habitats in the landscape, especially across large scales. We tested how mean field size and functional crop diversity affect farmland bird diversity and abundance over three consecutive years, and how these effects are modulated by the amount of small woody features (SWF) in the landscape. We related data from a national bird monitoring scheme to field‐level information from a novel, high‐resolution remote sensing‐based crop type map. Smaller field sizes and higher functional crop diversity were not generally associated with a higher diversity or abundance of farmland birds. Associations varied with species' breeding habitat preferences and were modulated by the amount of SWF. In landscapes with a low SWF amount, species diversity and the abundance of species breeding in field edges or shrubs were negatively associated with increasing field size. However, where the amount of SWF was high, larger field size was associated with higher species diversity and abundance of field and shrub breeders. Diversity increased with higher functional crop diversity, as did the abundance of non‐field breeders in landscapes with a medium to high SWF amount. Field size tended to have a stronger effect on bird diversity and abundance than functional crop diversity. Policy implications: National and EU agricultural policies should adopt a landscape perspective by considering the amount of semi‐natural habitats when designing biodiversity‐enhancing measures that target field size and functional crop diversity. In landscapes with low SWF amount, decreasing field sizes may be particularly effective to promote farmland bird diversity and the abundance of non‐field breeders. In landscapes with a medium to high SWF amount, increasing functional crop diversity is likely more effective than reducing field sizes. Field and shrub breeders may be promoted by maintaining landscapes with large fields, only if these offer a high SWF amount, low agronomic yield potential and low productivity.

Multi-source information fusion-driven corn yield prediction using the Random Forest from the perspective of Agricultural and Forestry Economic Management

The objective of this study is to promptly and accurately allocate resources, scientifically guide grain distribution, and enhance the precision of crop yield prediction (CYP), particularly for corn, along with ensuring application stability. The digital camera is selected to capture the digital image of a 60 m × 10 m experimental cornfield. Subsequently, the obtained data on corn yield and statistical growth serve as inputs for the multi-source information fusion (MSIF). The study proposes an MSIF-based CYP Random Forest model by amalgamating the fluctuating corn yield dataset. In relation to the spatial variability of the experimental cornfield, the fitting degree and prediction ability of the proposed MSIF-based CYP Random Forest are analyzed, with statistics collected from 1-hectare, 10-hectare, 20-hectare, 30-hectare, and 50-hectare experimental cornfields. Results indicate that the proposed MSIF-based CYP Random Forest model outperforms control models such as support vector machine (SVM) and Long Short-Term Memory (LSTM), achieving the highest prediction accuracy of 89.30%, surpassing SVM and LSTM by approximately 13.44%. Meanwhile, as the experimental field size increases, the proposed model demonstrates higher prediction accuracy, reaching a maximum of 98.71%. This study is anticipated to offer early warnings of potential factors affecting crop yields and to further advocate for the adoption of MSIF-based CYP. These findings hold significant research implications for personnel involved in Agricultural and Forestry Economic Management within the context of developing agricultural economy.

Dosimetry verification of in vitro radiotherapy dose via laser polishing of 3D-printed metallic implant surface

Titanium alloys have been frequently used for medical implants. However, their presence can cause variability in radiation dose during radiotherapy, leading to potential complications. Herein, this work aims to explore the impact of 3D printed Ti6Al4V implants on the dose of 6MV X-ray in radiotherapy, through direct measurement in the ionization chamber. The findings indicate that the absorption effect of titanium alloy implants lowers the dose behind the implants, while the backscattering effect increases the dose in front of the implants. It is demonstrated that the size, thickness, and mesh density of the titanium alloy implant show no significant effect on the dose in front of the implants. Nonetheless, it is found that the dose behind the implants increases with mesh density and decreases with implant thickness. Laser polishing is implemented as a surface modification technique for titanium implants, resulting in significantly improved implant surface smoothness, a reduction of the surface roughness, a decrease in defects and an alteration in the elemental composition percentage. Furthermore, the reduction in surface roughness leads to a transition towards a hydrophilic implant surface, which also leads to the enhancement of specular reflection and the reduction of diffuse scattering on the implant surface, thus producing a complex influence on the radiation dose. It is also revealed that at a constant X-ray irradiation energy, the dose values in front of and behind the implant both exhibit a declining trend as the irradiation field size increases. Finally, the existence of a dose compensation effect of scattered radiation on the primary radiation during radiotherapy is confirmed. This work provides important reference for clinical practice, aiding medical professionals in formulating precise treatment plans, optimizing the efficacy of radiotherapy, and minimizing side effects.

Determination of small-field output factors for beam-matched linear accelerators using various detectors and comparison of detector-specific output correction factors using IAEA Technical Report Series 483 protocol.

Beam matching is widely used to ensure that linear accelerators used in radiotherapy have equal dosimetry characteristics. Small-field output factors (OF) were measured using different detectors infour beam-matched linear accelerators and the measured OFs were compared with existing treatment planning system (TPS) Monte Carlo algorithm calculated OFs. Three Elekta Versa HDTM and one Elekta InfinityTMlinear accelerators with photon energies of 6 MV flattening filter (FF), 10 MVFF, 6 MV flattening filter free (FFF) and 10 MVFFF were used in this study. All the Linac'swere beam-matched, Dosimetry beam data were ± 1% compare with Reference Linac. Ten different type of detectors (four ionizationchambers and six diode detectors) were used for small-field OF measurements. The OFs were measured for field sizes of 1 × 1 to 10 × 10 cm2, and normalized to 10 × 10 cm2 field size. The uncorrected and corrected OFs were calculated from these measurements. The corrected OF was compare with existing treatment planning system (TPS) Monte Carlo algorithm calculated OFs. The small-field corrected and Uncorrected OF variations among the linear accelerators was within 1% for all energies and detectors. An increase in field size led to a reduction in the difference between OFs among the detectors, which was the case for all energies. The RSD values decreased with increasing field size. The TRS 483 provided Detector-specificoutput-correction factor (OCF) reduced uncertainty in small-field measurements. It is necessary to implement the OF-correction of small fields in a TPS. Special care must be taken to incorporate the corrected small-field OF in a TPS.

Potential to reduce pesticides in intensive apple production through management practices could be challenged by climatic extremes

Apples are the third most produced fruit in the world, but their production is often pesticide-intensive. Our objective was to identify options for pesticide reduction using farmer records from 2549 commercial apple fields in Austria during five years between 2010 and 2016. Using generalized additive mixed modeling, we examined how pesticide use was related to farm management, apple varieties, and meteorological parameters, and how it affected yields and toxicity to honeybees. Apple fields received 29.5 ± 8.6 (mean ± SD) pesticide applications per season at a rate of 56.7 ± 22.7 kg ha−1, which included a total of 228 pesticide products with 80 active ingredients. Over the years, fungicides accounted for 71 % of the pesticide amounts applied, insecticides for 15 %, and herbicides for 8 %. The most frequently used fungicides were sulfur (52 %), followed by captan (16 %) and dithianon (11 %). Of insecticides, paraffin oil (75 %) and chlorpyrifos/chlorpyrifos-methyl (6 % combined) were most frequently used. Among herbicides, glyphosate (54 %), CPA (20 %) and pendimethalin (12 %) were most often used. Pesticide use increased with increasing frequency of tillage and fertilization, increasing field size, increasing spring temperatures, and drier summer conditions. Pesticide use decreased with increasing number of summer days with maximum temperatures >30 °C and number of warm, humid days. Apple yields were significantly positively related to the number of heat days, warm humid nights, and pesticide treatment frequency, but were not affected by frequency of fertilization and tillage. Honeybee toxicity was not related to insecticide use. Pesticide use and yield were significantly related to apple varieties. Our analysis shows that pesticide use in the apple farms studied can be reduced by less fertilization and tillage, partly because yields were >50 % higher than the European average. However, weather extremes related to climate change, such as drier summers, could challenge plans to reduce pesticide use.

Adapting hippocampus multi-scale place field distributions in cluttered environments optimizes spatial navigation and learning.

Extensive studies in rodents show that place cells in the hippocampus have firing patterns that are highly correlated with the animal's location in the environment and are organized in layers of increasing field sizes or scales along its dorsoventral axis. In this study, we use a spatial cognition model to show that different field sizes could be exploited to adapt the place cell representation to different environments according to their size and complexity. Specifically, we provide an in-depth analysis of how to distribute place cell fields according to the obstacles in cluttered environments to optimize learning time and path optimality during goal-oriented spatial navigation tasks. The analysis uses a reinforcement learning (RL) model that assumes that place cells allow encoding the state. While previous studies have suggested exploiting different field sizes to represent areas requiring different spatial resolutions, our work analyzes specific distributions that adapt the representation to the environment, activating larger fields in open areas and smaller fields near goals and subgoals (e.g., obstacle corners). In addition to assessing how the multi-scale representation may be exploited in spatial navigation tasks, our analysis and results suggest place cell representations that can impact the robotics field by reducing the total number of cells for path planning without compromising the quality of the paths learned.

Hybrid pencil beam model based on photon characteristic line algorithm for lung radiotherapy in small fields

Abstract Hybrid pencil beam model (HPBM) based on photon characteristic line algorithm has been presented to get accurate three-dimensional (3D) dose distribution for lung radiotherapy in small fields. In the model, we introduced a scattering factor to accurately describe the transport behavior of scattered photons and secondary electrons, combined with the equivalent depth correction and the weighted density correction. The pencil beam kernels of heterogeneous lung phantoms were redefined by the scattering factor and depth dose for a reference field by photon characteristic line algorithm. Subsequently, the 3D dose distribution in lung phantoms with density of 0.1, 0.26, and 0.4 g/cm3, was calculated by the Finite-size pencil beam algorithm in five regular fields and an irregular field for 6 MV photon beam. The dose distributions obtained by the HPBM are in agreement with those obtained by the MC simulations, with a relative error of less than 3% in most of the cases. However, there are apparent discrepancies at media interfaces and lung anterior portion. Moreover, at media interfaces, relative dose errors of the two methods decrease with the increase in field size and lung density. The depth range in which relative errors is greater than 3% increases with the increase in field size at lung anterior portion. In these examples, maximum relative errors are between 5 and 29%. Nevertheless, it is shown that the HPBM based on photon characteristic line algorithm has potential research values in lung dose calculation under conditions of small fields.

Spatiotemporal dynamics and anthropologically dominated drivers of chlorophyll-a, TN and TP concentrations in the Pearl River Estuary based on retrieval algorithm and random forest regression

Estimation of large-scale and high-precision water quality parameters is critical in explaining the spatiotemporal dynamics and the driving factors of water quality variability, especially in areas with environmental complexity (e.g., crisscrossing waterways, high flood risk in rainy season and seawater invasion). Thus, in this study, a retrieval algorithm was developed to predict chlorophyll-a (Chl-a), total nitrogen (TN) and total phosphorus (TP) concentrations in the Pearl River Estuary (PRE) based on a large amount of in situ measurements and Landsat 8 remote sensing images. Random Forest (RF) machine learning was conducted to identify the relationship between environmental indicators (pH, turbidity, conductivity, total dissolved solids and water temperature), Chl-a, TN and TP. The results showed that the NIR/R Binomial algorithm for Chl-a estimation presented appreciable reliability with R2 of 0.7429, root mean square error (RMSE) of 1.2089 and mean absolute percent error (MAPE) of 15.33%. The water quality variation in the PRE showed a characteristic of overall improvement and regional deterioration with average concentrations of 7.28 μg/L, 1.15 mg/L and 0.12 mg/L for Chl-a, TN, and TP respectively. Turbidity and pH were identified as the most important indicators to explain Chl-a (52.86%, 39.91%), TN (52.38%, 40.57%) and TP (55.23%, 40.03%) variation. Agricultural pollution was the main pollution source due to the intensive application of fertilizer and increased field size. Besides, land use patterns (e.g., increasing farmland but decreasing forest) greatly influenced water quality from 2010 to 2020. Moreover, light limitation caused by high turbidity reduced the algae productivity and further lowered the Chl-a concentration. The driving factors for regional water quality variations were anthropologically dominated and supplemented by climate change. This study improved the monitoring accuracy of regional water environment and provided quantitative early warning of water pollution events for environmental practitioners, so as to achieve long-term monitoring, precise pollution management and efficient water resources management.

Increasing crop field size does not consistently exacerbate insect pest problems

Increasing diversity on farms can enhance many key ecosystem services to and from agriculture, and natural control of arthropod pests is often presumed to be among them. The expectation that increasing the size of monocultural crop plantings exacerbates the impact of pests is common throughout the agroecological literature. However, the theoretical basis for this expectation is uncertain; mechanistic mathematical models suggest instead that increasing field size can have positive, negative, neutral, or even nonlinear effects on arthropod pest densities. Here, we report a broad survey of crop field-size effects: across 14 pest species, 5 crops, and 20,000 field years of observations, we quantify the impact of field size on pest densities, pesticide applications, and crop yield. We find no evidence that larger fields cause consistently worse pest impacts. The most common outcome (9 of 14 species) was for pest severity to be independent of field size; larger fields resulted in less severe pest problems for four species, and only one species exhibited the expected trend of larger fields worsening pest severity. Importantly, pest responses to field size strongly correlated with their responses to the fraction of the surrounding landscape planted to the focal crop, suggesting that shared ecological processes produce parallel responses to crop simplification across spatial scales. We conclude that the idea that larger field sizes consistently disrupt natural pest control services is without foundation in either the theoretical or empirical record.

Environmentally friendly landscape management improves oilseed rape yields by increasing pollinators and reducing pests

Abstract Pollination and pest control are two major ecological functions sustaining crop yield. In insect‐pollinated crops, previous studies have revealed that an increase in resources and habitats in landscapes can increase pest control by natural enemies as well as insect pollination by pollinators. However, data have been lacking that simultaneously considers the effects of landscape on both pollinators and pests, and the direct and indirect effects on yields of farming practices interacting with landscape, bees and pests. This study aimed to fill this gap by focusing on oilseed rape (OSR), an insect‐pollinated crop of high economic value. We first quantified the effects of landscape and farming practices on both bee and pest abundance caught in OSR blooming season in 124 farmed fields over a 6‐year study (~20 fields sampled per year), and then used structural equation modelling to assess the direct and indirect links between bees, pests, farming practices and landscape on yield. The results showed that landscape had a stronger effect on bee and pest abundance than agrochemical farming practices. Bees and pests decreased with the amount of OSR in the landscape surrounding the focal field, and showed contrasted effects with the amount of meadow and organic farming: positive for bees and negative for pests. Bee abundance also increased with the amount of sunflower in the landscape the preceding year, and decreased with increasing field size. While agrochemicals surprisingly had barely any effect on bees and pests, their use improved OSR yield, although at a similar magnitude as bee and pest abundances. Synthesis and application. This study, conducted in commercial crop fields, underlines the important contribution of sustainable landscape management for enhancing OSR yield. Despite agrochemicals' ability to improve or maintain OSR yields, their unconditional use is unsustainable due to negative externalities. Therefore, alternative options such as those highlighted in our study—such as reducing field size, increasing the amount of organic farming in the landscape, or sowing OSR in landscapes rich in sunflowers the preceding year—appear to be relevant tools to promote ecosystem services, maintain yield and conserve biodiversity. These findings support the potential of nature‐based solutions to foster more sustainable agriculture.

Responses of selected beetle families (Carabidae, Chrysomelidae, Curculionidae) to non-crop habitats in an agricultural landscape

Agricultural intensification has caused a simplification of agricultural landscapes, accompanied by increasing field sizes and a reduction of non-crop habitats. To mitigate negative impacts of intensification, it is necessary to understand to what extent different non-crop habitats contribute to the maintenance of biodiversity in agroecosystems. Here, we compared the taxonomic diversity of three beetle families among four habitat types—wheat fields, grassy field margins, wildflower-sown areas under power poles, and permanent grassland fallows, in an agricultural landscape in western Germany. Carabidae were caught by pitfall trapping, Chrysomelidae and Curculionidae by suction sampling. We found surprisingly little variation among habitat types, though the rarefied species number tended to be higher in grassland fallows and field margins than under power poles and in wheat fields. Nevertheless, species assemblages differed substantially among habitat types. In Carabidae, grassland fallows were dominated by hygrophilous species with poor dispersal ability as opposed to all other habitat types being dominated by open landscape species with high dispersal ability. In Chrysomelidae and Curculionidae, power pole islands differed from the other habitat types with predominantly open landscape species, whereas wheat fields and grassland fallows were clearly dominated by eurytopic species. Our results thus highlight the need for a combination of different conservation measures for enhancing the functional diversity of beetle assemblages.

Impact of landscape design on the greenhouse gas emissions of shrub willow bioenergy buffers in a US Midwest corn‐production landscape

AbstractPrevious studies have evaluated the economics and ecosystem services of perennial bioenergy crops when replacing grain crops on marginal (environmentally critical and/or underproductive) lands. This study used life‐cycle analysis (LCA) to investigate the greenhouse gas (GHG) emissions of perennial crops when grown in targeted landscape positions and their impact in reducing nitrogen leaching. Specifically, LCA was performed to evaluate the GHG emissions of growing shrub willow on marginal lands in the Indian Creek watershed in Illinois to assess the sustainability of strategically planted willow buffer strips. Willow was grown as a short‐rotation woody crop with a 21‐year rotation under three scenarios including a business‐as‐usual (BAU) field‐scale production with nitrogen fertilizer application and two unfertilized subfield buffer scenarios – landscape single subfield (LSSF) or landscape multiple subfields (LMSF) – grown alongside cornfields to reduce nitrate leaching. Each scenario also considers three field sizes, 2.0, 10.1, and 40.5 ha. The average annual GHG emissions from willow production and depot transportation were 0.32–0.77 Mg‐CO2e ha−1 with the lowest emissions for the LSSF scenario and highest for the BAU. The GHG emissions for the LSSF and BAU scenarios are independent of field size, whereas LMSF emissions increase with increasing field size, 0.41 Mg‐CO2e ha−1 at 2.0 ha and 0.76 Mg‐CO2e ha−1 at 40.5 ha. Emission results were most sensitive to the willow yield, followed by fertilizer application rate (BAU only), harvest fuel consumption, and transportation distance. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd

KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation.

Most methods for medical image segmentation use U-Net or its variants as they have been successful in most of the applications. After a detailed analysis of these "traditional" encoder-decoder based approaches, we observed that they perform poorly in detecting smaller structures and are unable to segment boundary regions precisely. This issue can be attributed to the increase in receptive field size as we go deeper into the encoder. The extra focus on learning high level features causes U-Net based approaches to learn less information about low-level features which are crucial for detecting small structures. To overcome this issue, we propose using an overcomplete convolutional architecture where we project the input image into a higher dimension such that we constrain the receptive field from increasing in the deep layers of the network. We design a new architecture for im- age segmentation- KiU-Net which has two branches: (1) an overcomplete convolutional network Kite-Net which learns to capture fine details and accurate edges of the input, and (2) U-Net which learns high level features. Furthermore, we also propose KiU-Net 3D which is a 3D convolutional architecture for volumetric segmentation. We perform a detailed study of KiU-Net by performing experiments on five different datasets covering various image modalities. We achieve a good performance with an additional benefit of fewer parameters and faster convergence. We also demonstrate that the extensions of KiU-Net based on residual blocks and dense blocks result in further performance improvements. Code: https://github.com/jeya-maria-jose/KiU-Net-pytorch.

An approach for comparing agricultural development to societal visions

There is broad agreement that agriculture has to become more sustainable in order to provide enough affordable, healthy food at minimal environmental and social costs. But what is “more sustainable”? More often than not, different stakeholders have opposing opinions on what a more sustainable future should look like. This normative dimension is rarely explicitly addressed in sustainability assessments. In this study, we present an approach to assess the sustainability of agricultural development that explicitly accounts for the normative dimension by comparing observed development with various societal visions. We illustrate the approach by analyzing farm- and landscape-scale development as well as sustainability outcomes in a Swiss case study landscape. Observed changes were juxtaposed with desired changes by Avenir Suisse, a liberal think tank representing free-market interests; the Swiss Farmers Association, representing a conservative force; and Landwirtschaft mit Zukunft, an exponent of the Swiss agroecological movement. Overall, the observed developments aligned most closely with desired developments of the liberal think-tank (72%). Farmer interviews revealed that in the case study area farms increased in size (+ 57%) and became more specialized and more productive (+ 223%) over the past 20 years. In addition, interpretation of aerial photographs indicated that farming became more rationalized at the landscape level, with increasing field sizes (+ 34%) and removal of solitary field trees (− 18%). The case study example highlights the varying degrees to which current developments in agriculture align with societal visions. By using societal visions as benchmarks to track the progress of agricultural development, while explicitly addressing their narratives and respective systems of values and norms, this approach offers opportunities to inform also the wider public on the extent to which current developments are consistent with different visions. This could help identify mismatches between desired and actual development and pave the way for designing new policies.

Effectiveness of Multifunctional Margins in Insect Biodiversity Enhancement and RTE Species Conservation in Intensive Agricultural Landscapes

Starting in the 1950s, agricultural production has been remarkably intensified, resulting in modern management systems where a severe increase in field size led to an elimination of edges and other ecologically valuable structural elements. The resulting habitat loss caused dramatic changes in natural communities. The aim of this work is to test whether there are statistically significant differences in insect abundance over time by using multifunctional margins that are seed mixtures of autochthonous species planted in combined strips, which are the fastest way to provide significant biodiversity benefits within farmed landscapes, enhancing the diversity and abundance of insects, birds, and small mammals, offering resources and reservoirs. This study was carried out in three intensive fruit farms in Spain over a three-year period (2013–2015). Each field was divided into two zones: the margin where a multifunctional margin was planted, and another that remained unchanged in the field. A clear trend to increase RTE species throughout the years in all farms was observed. Moreover, the margin showed a significant difference with respect to the field in the average number of insect species and individuals. The use of margins improves the appearance of RTE species in mean percentages ranging between 12.06 and 25.26% according to the sampling area. Margins also favour the increase in species (148.83–232.84%) and individuals (207.24–586.70%) in agricultural landscapes. These results clearly show that margins are an essential tool to fight insect decline in intensive farming areas.

Evaluation of the ability of three commercially available dosimeters to detect systematic delivery errors in step-and-shoot IMRT plans.

There is limited data on error detectability for step-and-shoot intensity modulated radiotherapy (sIMRT) plans, despite significant work on dynamic methods. However, sIMRT treatments have an ongoing role in clinical practice. This study aimed to evaluate variations in the sensitivity of three patient-specific quality assurance (QA) devices to systematic delivery errors in sIMRT plans. Four clinical sIMRT plans (prostate and head and neck) were edited to introduce errors in: Multi-Leaf Collimator (MLC) position (increasing field size, leaf pairs offset (1-3 mm) in opposite directions; and field shift, all leaves offset (1-3 mm) in one direction); collimator rotation (1-3 degrees) and gantry rotation (0.5-2 degrees). The total dose for each plan was measured using an ArcCHECK diode array. Each field, excluding those with gantry offsets, was also measured using an Electronic Portal Imager and a MatriXX Evolution 2D ionisation chamber array. 132 plans (858 fields) were delivered, producing 572 measured dose distributions. Measured doses were compared to calculated doses for the no-error plan using Gamma analysis with 3%/3 mm, 3%/2 mm, and 2%/2 mm criteria (1716 analyses). Generally, pass rates decreased with increasing errors and/or stricter gamma criteria. Pass rate variations with detector and plan type were also observed. For a 3%/3 mm gamma criteria, none of the devices could reliably detect 1 mm MLC position errors or 1 degree collimator rotation errors. This work has highlighted the need to adapt QA based on treatment plan type and the need for detector specific assessment criteria to detect clinically significant errors.

Investigation of backscatter factor in medical radiography using anthropomorphic phantom by optically stimulated luminescence dosimeter

At the diagnostic reference level (DRL) related to medical radiation, DRL quantity for general radiography is the entrance surface dose (ESD). Calculation of the ESD in medical radiography requires the backscatter factor (BSF), but derivation of the BSF requires assessment of an irradiated simulation of a human body. The present study used optically stimulated luminescence (OSL) dosimeters and an anthropomorphic phantom as the irradiated body, and the BSF was calculated for different half value layer (HVL)s and field sizes. The need for different BSFs for different regions was also investigated by derivationing of the BSFs for different regions. The pelvis of a RANDO phantom was irradiated under the conditions of the HVL of 2.0, 3.1, and 4.6 mmAl; tube current of 200 mA; irradiation time of 0.1 s; source surface distance of 100 cm; and field sizes of 10 × 10 cm2, 20 cm2, 30 cm2, and 40 cm2. Measurement in air was performed under the same conditions. Several threads were stretched through the air with tissue paper placed on them and the nanoDot dosimeters placed on the paper. Four dosimeters were placed, and measurement was performed 5 times under each set of conditions. The compared radiographed regions were the skull, chest, and pelvis. The BSF increased with increasing HVL size and with increasing field size. The larger the HVL, the larger the difference between field sizes of 10 × 10 cm2 and 40 × 40 cm2 and the larger the increase in BSF relative to the increase in field size. The BSF differed by region, from large to small in the order chest, pelvis, and skull. The results thus showed that the BSF differs by the radiographed region. Thus, it is desirable to determine the BSF in each radiographed region by investigation with an anthropomorphic phantom.

Measurement and Calculation of Electron Contamination for Radiotherapy Photon Mode

Context: This study was done to review the electron contamination sources and measurement based on dosimetry and simulation techniques for radiotherapy and also to investigate factors affecting electron contamination reduction. Methods: We systematically searched five major indexing databases, including PubMed, Scopus, Embase, ISI web of science, and Cochrane central, using keywords of electron contamination, electron contamination AND measurement, electron contamination AND simulation, and electron contamination AND reduction until Dec 2020. Results: Overall, 35 studies were reviewed, including articles reporting the theory of electron contamination, papers on dosimetry methods to measure electron contamination, studies about simulation methods to assess electron contamination, and articles about reducing electron contamination. The results indicated an increase in electron contamination using a flattering filter, an increase in field size, the presence of prosthesis in the patient's body, and a rise in photon energy. Conclusions: It can be concluded that the excessive delivered doses by electron contamination can cause skin complications, such as erythema, desquamation, and telangiectasia inside or outside the photon field. The amount of electron contamination depends on factors, such as radiation field size, beam energy, and materials placed in the photon path. Electron contamination can be decreased by increasing the source distance to the point of measurement by the dosimeter, applying a lead foil, magnetic deflector, or replacing a portion of air column between patient and radiotherapy system head by helium gas, and also limiting the treatment field.