Field Size Research Articles

Magnetically targeted lidocaine sustained-release microspheres: optimization, pharmacokinetics, and pharmacodynamic radius of effect

ObjectiveThis study aimed to optimize the formulation of magnetically targeted lidocaine microspheres, reduce the microsphere particle size, and increase the drug loading and encapsulation rate of lidocaine. The optimized microspheres...

Analisis Distribusi Dosis pada Treatment Planning System Pasien Kanker Payudara dengan Sumber Foton 6 MV pada Instalasi Radioterapi Rumah Sakit X

The internship at X Hospital aimed to gain practical experience as a medical physicist over two months, particularly in the treatment planning system activities in the radiotherapy unit. Additionally, this internship aimed to evaluate the Dose Volume Histogram (DVH) and analyze the effectiveness of the isodose lines. The treatment planning system is a simulation of cancer or tumor treatment using radiation with 3D conformal radiotherapy (3D-CRT) techniques. The patient study object was a woman with post-mastectomy breast cancer who was to undergo adjuvant curative therapy. The prescribed dose was 50 Gy, divided into 25 fractions, using a 6 MV photon source. The irradiation was conducted with four fields, gantry angle 129° with collimator angle 270°, 310° with collimator angle 90°, 130° with collimator angle 0°, and 270° with collimator angle 0°, field size 14 x 14 cm, and irradiation distance of 100 cm. The TPS simulation results indicated that the dose received by the Planning Target Volume (PTV) covered more than 90% of the target volume (special treatment), while the dose received by the Organ at Risk (OAR) tended to be below the threshold limit, and the isodose lines ensured optimal radiation dose distribution to the breast cancer target area. This was demonstrated by the DVH curve.

A review of diamond dosimeters in advanced radiotherapy techniques.

This review article synthesizes key findings from studies on the use of diamond dosimeters in advanced radiotherapy techniques, showcasing their applications, challenges, and contributions to enhancing dosimetric accuracy. The article explores various dosimeters, highlighting synthetic diamond dosimeters as potential candidates especially due to their high spatial resolution and negligible ion recombination effect. The clinically validated commercial dosimeter, PTW microDiamond (mD), faces limitations in small fields, proton and hadron therapy and ultra-high dose per pulse (UHDPP) conditions. Variability in reported values for field sizes 2 2 is noted, reflecting the competition between volume averaging and density perturbation effects. PTW's introduction of flashDiamond (fD) holds promise for dosimetric measurements in UHDPP conditions and is reliable for commissioning ultra-high dose rate (UHDR) electron beam systems, pending the clinical validation of the device. Other advancements in diamond detectors, such as in 3D configurations and real-time dose per pulse x-ray detectors, are considered valuable in overcoming challenges posed by modern radiotherapy techniques, alongside relative dosimetry and pre-treatment verifications. The studies discussed collectively provide a comprehensive overview of the evolving landscape of diamond dosimetry in the field of radiotherapy, and offer insights into future directions for research and development in thefield.

Nonrigid registration method for longitudinal chest CT images in COVID-19

Rationale and objectivesTo analyze morphological changes in patients with COVID-19-associated pneumonia over time, a nonrigid registration technique is required that reduces differences in respiratory phase and imaging position and does not excessively deform the lesion region. A nonrigid registration method using deep learning was applied for lung field alignment, and its practicality was verified through quantitative evaluation, such as image similarity of whole lung region and image similarity of lesion region, as well as visual evaluation by a physician. Materials and methodsFirst, the lung field positions and sizes of the first and second CT images were roughly matched using a classical registration method based on iterative calculations as a preprocessing step. Then, voxel-by-voxel transformation was performed using VoxelMorph, a nonrigid deep learning registration method. As an objective evaluation, the similarity of the images was calculated. To evaluate the invariance of image features in the lesion site, primary statistics and 3D shape features were calculated and statistically analyzed. Furthermore, as a subjective evaluation, the similarity of images and whether nonrigid transformation caused unnatural changes in the shape and size of the lesion region were visually evaluated by a pulmonologist. ResultsThe proposed method was applied to 509 patient data points with high image similarity. The variances in histogram characteristics before and after image deformation were confirmed. Visual evaluation confirmed the agreement between the shape and internal structure of the lung field and the natural deformation of the lesion region. ConclusionThe developed nonrigid registration method was shown to be effective for quantitative time series analysis of the lungs.

Beam profile characteristics of a Varian linear accelerator across different photon energy levels

Radiotherapy employs variety of energy radiation to destroy cancer cells. A linear accelerator(also called LINAC) is the machine used to delivered external beam radiation therapy.In order to confirm the treatment planning systems that deliver the best radiation to the tumors while sparing the surrounding normal tissues, extensive measurements of dosimetric parameters are part of the commissioning procedure of a LINAC for clinical usage. This work aimed to compare and assess photon beam profiles with respect to penumbra width, symmetry, and beam flatness. Beam profile measurements were performed for this study atTMSS Cancer Center, Bogura, Bangladesh, using a linear accelerator (Varian VitalBeam SN: 5199) with 6MV,10MV and 15MV photon energies for a set of field sizes (4 × 4, 10 × 10 and 20 × 20 cm2) and various reference depths keeping the same environmental conditions. A 3D water phantom, CC13 ionization chamber (SN:18635)as a reference chamber, CC04 ionization field chamber (SN:18616) as a and IBA myQA Accept software version 1.6 were used to measure the profiles of photon energies 6 MV, 10 MV 15 MV respectively. Utilizing the Eclipse (Version: 16.1) external treatment planning system, the profile calculation was carried out. According to the manufacturer's and IEC specifications, the photon beam profile data from the current investigation are compatible, and all of the tolerances fall within the ranges of clinically acceptable tolerance.

Magnetic field enhanced laser absorption on a metallic surface incorporated with shape-dependent nanostructures

Abstract This communication proposes an analytical model to investigate the nanoparticle-based nonlinear absorption phenomenon associated with an obliquely incident p-polarized laser beam on a metallic surface. In this scheme, the surface is ingrained with noble-metal spherical nanoparticles and cylindrical nanoparticles in the presence of an external static magnetic field. The absorption of laser energy in the presence of nanoparticles (NPs) is attributed to surface plasmon resonance and enhanced magnetic-field effects. The absorption phenomenon is significantly enhanced by the incorporation of nanostructures and a magnetic field. The ellipticity characterizing parameter, which significantly influences the resonant frequency of different nanometric structures, has also been analysed and discussed. The effects of varying the magnetic field intensity, incident angle, size, and spacing of the NP were examined to determine their influence on the anomalous absorption of the laser. Furthermore, a direct dependency was found between the absorption coefficient and transmission coefficient of the incident laser, as well as the dimensions of the NPs. Several applications have direct relevance to this study, including biosensors such as DNA sensors and immunosensors, photothermal therapy, photoacoustic imaging, optoelectronic devices, solar cells, and surface-enhanced Raman spectroscopy.

Comparison of directly and indirectly estimated entrance skin dose (ESD) for diagnostic radiation qualities (RQR, RQA and RQT) using water phantom and shadowfree diagnostic chamber (SFD)

BackgroundThe aim of this study was to find the entrance skin dose (ESD) for diagnostic radiation qualities RQRs, RQAs and RQTs given in IAEA technical report series No. 457 using direct and indirect methods of measurement. Measurements were done for 5 × 5, 10 × 10, 15 × 15, 20 × 20 and 25 × 25 cm2 field sizes and 70, 80, 90 and 100 cm source to surface distance (SSD) using shadow-free diagnostic (SFD) chamber and water phantom having dimension 30 × 30 × 30 cm3. ESD direct measurements were done by placing SFD chamber on the surface of water phantom, while in the case of indirect measurements, air kerma values were obtained.ResultsESD values for different selected radiation qualities RQR2, RQR5, RQR8, RQR10, RQA2, RQA5, RQA8, RQA10, RQT8, RQT9 and RQT10 were found to be in the range of 0.0045–5.11 mGy per examination.ConclusionsResults obtained were found to be comparable with ESD values published in the literature. The obtained results in this research would help in establishing the national diagnostic reference levels (DRLs) which would help in the optimization of diagnostic imaging procedures. It would also help the radiographers to optimize field sizes and SSDs in order to reduce dose to the patients thereby ensuring good radiological practices, and this would reduce the stochastic risk to the patients caused by the ionizing radiations.

Homotopy properties of the complex of frames of a unitary space

AbstractLet be a finite‐dimensional vector space equipped with a nondegenerate Hermitian form over a field . Let be the graph with vertex set the one‐dimensional nondegenerate subspaces of and adjacency relation given by orthogonality. We give a complete description of when is connected in terms of the dimension of and the size of the ground field . Furthermore, we prove that if , then the clique complex of is simply connected. For finite fields , we also compute the eigenvalues of the adjacency matrix of . Then, by Garland's method, we conclude that for all , where is a field of characteristic 0, provided that . Under these assumptions, we deduce that the barycentric subdivision of deformation retracts to the order complex of the certain rank selection of that is Cohen–Macaulay over . Finally, we apply our results to the Quillen poset of elementary abelian ‐subgroups of a finite group and to the study of geometric properties of the poset of nondegenerate subspaces of and the poset of orthogonal decompositions of .

Analysis of the relationship between field size and change in radiation dose to patient and staff based on radiographic technique in fluoroscopy and radiography

Analysis of the relationship between field size and change in radiation dose to patient and staff based on radiographic technique in fluoroscopy and radiography

Assessing The Impact of Rising Cost of Materials On Construction Activities in Enugu, Enugu State, Nigeria

This study focused on assessing the impact of rising cost of building materials on construction activities in Enugu, Enugu state, Nigeria. The aim of this study is to assess the impact of rising cost of materials on construction activities in Enugu, Nigeria in order to proffer a solution to the rise in the cost of these materials used in everyday construction in Enugu state. With the following objectives; to identify the factors that lead to increasing cost of material in Enugu State, Nigeria; to assess the impact of rising cost of materials on construction activities in Enugu; to proffer solutions to the rise in the cost of building materials. The research design employed was primary and secondary which encompasses descriptions and quantitative analysis on a randomly selected sample of receipt of building materials from the suppliers over the years. The population of the study is 223 professionals in the field and sample size of 143 which was gotten using Taro Yamane formula. The findings of the study reveals that the factors that lead to increasing cost on the building construction activities in Enugu State are; fluctuations in material costs, design changes and scope creep, regulatory compliance and permitting, project delays, weather and environmental factors, technology and innovation costs, interest rates and financing costs, and others. Finally, the study recommends that there will be need for relevant authorities in the building industry to re-examine and educate the people on its existence and equally generate the possible ways of reducing the increasing cost of building materials so as to enhance the building construction industry in Nigeria.

Design and assessment of a concentrating solar thermal system for industrial process heat with a copper slag packed-bed thermal energy storage

Decarbonising the industrial sector is a key part of climate change mitigation targets, and Solar Heat for Industrial Process (SHIP) is a promising technology to achieve this. However, one of the drawbacks of SHIP systems is that they rely on an intermittent energy source. Therefore, sensible energy storage has emerged as a potential solution. In addition, solid byproducts have been proposed as a low-cost but effective material for thermal energy storage (TES). This work presents a SHIP system model coupled with a copper slag-packed-bed TES (PBTES) model using air as heat transfer fluid. The TES has been implemented to preheat the makeup water of the tank where steam is generated. A system design was carried out using a parametric analysis to find a solar field size and a corresponding TES volume. The resulting system was simulated, and the operating variables were analysed in detail. The results show that it is possible to generate 20% more energy due to the storage system. Additionally, a techno-economic analysis indicates that the SHIP with PBTES system results in a payback period of 14 years and a savings of CO2 emissions of 30tCO2.

DiagSWin: A multi-scale vision transformer with diagonal-shaped windows for object detection and segmentation

Recently, Vision Transformer and its variants have demonstrated remarkable performance on various computer vision tasks, thanks to its competence in capturing global visual dependencies through self-attention. However, global self-attention suffers from high computational cost due to quadratic computational overhead, especially for the high-resolution vision tasks (e.g., object detection and semantic segmentation). Many recent works have attempted to reduce the cost by applying fine-grained local attention, but these approaches cripple the long-range modeling power of the original self-attention mechanism. Furthermore, these approaches usually have similar receptive fields within each layer, thus limiting the ability of each self-attention layer to capture multi-scale features, resulting in performance degradation when handling images with objects of different scales. To address these issues, we develop the Diagonal-shaped Window (DiagSWin) attention mechanism for modeling attentions in diagonal regions at hybrid scales per attention layer. The key idea of DiagSWin attention is to inject multi-scale receptive field sizes into tokens: before computing the self-attention matrix, each token attends its closest surrounding tokens at fine granularity and the tokens far away at coarse granularity. This mechanism is able to effectively capture multi-scale context information while reducing computational complexity. With DiagSwin attention, we present a new variant of Vision Transformer models, called DiagSWin Transformers, and demonstrate their superiority in extensive experiments across various tasks. Specifically, the DiagSwin Transformer with a large size achieves 84.4% Top-1 accuracy and outperforms the SOTA CSWin Transformer on ImageNet with 40% fewer model size and computation cost. When employed as backbones, DiagSWin Transformers achieve significant improvements over the current SOTA modules. In addition, our DiagSWin-Base model yields 51.1 box mAP and 45.8 mask mAP on COCO for object detection and segmentation, and 52.3 mIoU on the ADE20K for semantic segmentation.

Abnormal pattern recognition for online inspection in manufacturing process based on multi-scale time series classification

The collection of large volumes of temporal data during the production process is streamlined in a cyber manufacturing environment. The ineluctable abnormal patterns in these time series often serve as indicators of potential manufacturing faults. Consequently, the presence of effective analytical methods becomes essential for monitoring and recognizing these abnormal manufacturing patterns. However, the extensive process data may contain various minor abnormal patterns, typically reflecting changes in production status influenced by multiple anomalous causes. This study introduces an approach for recognizing abnormal manufacturing patterns through multi-scale time series classification (TSC). Long-term process signals undergo slicing using dynamically sized observation windows and subsequent classification at multiple scales employing our proposed TSC model, the distance mode profile-multi-branch dilated convolution network (DMP-MDNet). DMP-MDNet comprises two key modules aimed at bypassing complicated feature engineering and enhancing generalization capability. The first module, DMP, uses similarity measurement to encode scale- and magnitude-invariant temporal properties. Subsequently, the MDNet, equipped with multi-receptive field sizes, effectively leverages multi-granularity data for accurate classification. The effectiveness of our method is demonstrated through the analysis of a real-world body-in-white production dataset and various widely used public TSC datasets, showing promising applicability in actual manufacturing processes.

MsFNet: Multi-Scale Fusion Network Based on Dynamic Spectral Features for Multi-Temporal Hyperspectral Image Change Detection

With the development of satellite technology, the importance of multi-temporal remote sensing (RS) image change detection (CD) in urban planning, environmental monitoring, and other fields is increasingly prominent. Deep learning techniques enable a profound exploration of the intrinsic features within hyperspectral (HS) data, leading to substantial enhancements in CD accuracy while addressing several challenges posed by traditional methodologies. However, existing convolutional neural network (CNN)-based CD approaches frequently encounter issues during the feature extraction process, such as the loss of detailed information due to downsampling, which hampers a model’s ability to accurately capture complex spectral features. Additionally, these methods often neglect the integration of multi-scale information, resulting in suboptimal local feature extraction and, consequently, diminished model performance. To address these limitations, we propose a multi-scale fusion network (MsFNet) which leverages dynamic spectral features for effective multi-temporal HS-CD. Our approach incorporates a dynamic convolution module with spectral attention, which adaptively modulates the receptive field size according to the spectral characteristics of different bands. This flexibility enhances the model’s capacity to focus on critical bands, thereby improving its ability to identify and differentiate changes across spectral dimensions. Furthermore, we develop a multi-scale feature fusion module which extracts and integrates features from deep feature maps, enriching local information and augmenting the model’s sensitivity to local variations. Experimental evaluations conducted on three real-world HS-CD datasets demonstrate that the proposed MsFNet significantly outperforms contemporary advanced CD methods in terms of both efficacy and performance.

Modelling and optimization of concentrated solar power using response surface methodology: A comparative study of air, water, and hybrid cooling techniques

This research introduces a novel approach specifically designed to improve the design of Concentrated Solar Power plants utilizing the Response Surface Methodology. The objective of the suggested methodology is to enhance energy production efficiency by simultaneously minimizing the levelized cost of electricity and the land footprint associated with the power plant while comparing three different cooling techniques: air, water, and hybrid. Two software tools, System Advisor Model and Design-Expert, are employed to validate the primary model, evaluate the responses, generate the predictive models, and verify the results. The configuration of a Concentrated Solar Power plant is influenced by four main factors: the size of the solar field (solar multiple), row spacing, number of solar assemblies per loop, and size of thermal energy storage. In this study, these factors are varied within the following ranges: solar multiple from 1 to 5, row spacing from 10 to 30 m, number of solar assemblies from 4 to 10 per loop, and thermal energy storage from 5 to 15 h. The generated predictive models demonstrated very high accuracy, particularly for the annual energy production, with an error ranging between 0.2% and 1.5%. The findings showed that the hybrid cooling system is the most cost-effective cooling technique and has the highest energy output compared to the evaporative and air-cooling methods. When optimizing the required area of the hybrid cooled plant with a reduction of 47.44%, the analysis indicated a minimal decrease in energy output of 3.61% and a slight increase in the levelized cost of electricity by 0.95%. According to the results, the effect of area on the annual energy production and levelized cost of electricity is significant below the optimal area, while this effect becomes minor at higher values.

MR-OCTAVIUS 4D with 1500 MR and 1600 MR arrays is suitable for plan QA in a 1.5 T MRI-linac

To ensure the accuracy of radiation delivery to patients in a 1.5 T MRI-linac, the implementation of quality assurance (QA) devices compatible with MR technology is essential. The OCTAVIUS 4D MR, made by PTW (Freiburg, Germany) is designed to ensure consistent and ideal alignment of its detectors with the direction of each beam segment. This study focuses on investigating the fundamental characteristics of the detector response for the OCTAVIUS Detector (OD) 1500 MR and OCTAVIUS 1600 MR when used in the MR-compatible OCTAVIUS 4D. Characteristics examined included short-term reproducibility, dose linearity, field size dependency, monitor unit (MU) rate dependency, dose-per-pulse dependency, and angular dependency. The evaluation of OD 1500 MR also involved measuring 25 clinical treatment plans across diverse target sizes and anatomical sites, including the liver/pancreas, rectum, prostate, lungs, and lymph nodes. One plan was measured with the standard setup and with a 5 cm left offset. The OD 1600 MR was not available for these measurements. The capability of the OD 1500 MR to identify potential errors was assessed by introducing a MU and positional shift within the software. The results demonstrated no significant differences in short-term reproducibility ( <0.2% ), dose linearity ( <1% ), field size dependency ( <0.7% for field sizes larger than 5 cm × 5 cm), MU rate dependency ( <0.8% ), dose-per-pulse dependency ( <0.4% ) and angular dependency (standard deviation <0.5% ). All tests of clinical plans were successfully completed. The OD 1500 MR demonstrated compatibility with the standard 95% pass rate when employing a global 3%/3 mm gamma criterion, and a 90% pass rate using a global 2%/2 mm gamma criterion. The detector demonstrated the capacity to measure treatment plans with a 5 cm left offset. With the standard parameters, the gamma test was sensitive to position errors but required an addition tests of mean/median dose or point dose in order to detect small dose difference.

Dynamic range and optimization strategies for radiochromic film calibration using gradient radiation fields.

This investigation aimed to optimize gradient positioning for radiochromic film calibration to facilitate a uniform distribution of calibration points. The study investigated the influence of various parameters on gradient dose profiles generated by a physical wedge, assessing their impact on the field's dose dynamic range, a scalar quantity representing the span of absorbed doses. Numerical parameterization of the physical wedge profile was used to visualize and quantify the impact of field size, depth, and energy on the dynamic range of dose gradients. This concept enabled the optimization of the gradient positioning and estimation of the necessary number of exposures for the desired calibration dose range. An optimization algorithm based on histogram bin height minimization was developed and presented. The maximum dynamic range was achieved with a 20 20 field size at 5 cm depth. Optimization of wedge gradient positioning yielded the most uniform dose distribution with 7 exposures for the [1,10] Gy range and 8 exposures for the [1,20] Gy range. Film calibration using gradients centered at 1.6, 3, 3.5, and 7 Gy central axis (CAX), obtained through optimized gradient positioning, was showcased. The presented work demonstrates the potential for an improved film calibration process, with efficient material utilization and enhanced dosimetric accuracy for clinical applications. While the method was described for the use of a physical wedge, the methodology can be easily extended to the use of a more convenient dynamicwedge.

Commissioning an ultra-high-dose-rate electron linac with end-to-end tests

Objective. The FLASH effect can potentially be used to improve the therapeutic ratio of radiotherapy (RT) through delivery of Ultra-high-dose-rate (UHDR) irradiation. Research is actively being conducted to translate UHDR-RT and for this purpose the Mobetron is capable of producing electron beams at both UHDR and conventional dose rates for FLASH research and translation. This work presents commissioning of an UHDR Mobetron with end-to-end tests developed for preclinical research. Approach. UHDR electron beams were commissioned with an efficient approach utilizing a 3D-printed water tank and film to fully characterize beam characteristics and dependences on field size, pulse width (PW) and pulse repetition frequency (PRF). This commissioning data was used to implement a beam model using the GAMOS Monte Carlo toolkit for the preclinical research. Then, the workflow for preclinical FLASH irradiation was validated with end-to-end tests delivered to a 3D-printed mouse phantom with internal inhomogeneities. Main results. PDDs, profiles and output factors acquired with radiochromic films were precisely measured, with a PRF that showed little effect on the UHDR beam energy and spatial characteristics. Increasing PW reduced the D max and R50 by 2.08 mm µs−1 and 1.28 mm µs−1 respectively. An end-to-end test of the preclinical research workflow showed that both profiles in head-foot and lateral directions were in good agreement with the MC calculations for the heterogeneous 3D printed mouse phantom with Gamma index above 93% for 2 mm/2% criteria, and 99% for 3 mm/3%. Significance. The UHDR Mobetron is a versatile tool for FLASH preclinical research and this comprehensive beam model and workflow was validated to meet the requirements for conducting translational FLASH research.

Effect of Field Size Dependence on Dose Rate on Co-60 Teletherapy Unit at BINOR

Background: Cancer, defined as the uncontrolled proliferation of malignant cells, is a serious hazard. Radiotherapy, which employs high-energy radiation, seeks to break cancer cell DNA. Due to the significant consequences involved, accuracy is of utmost importance. Before commencing radiation therapy, thorough quality assurance procedures are carried out. The Percentage Depth Dose (PDD) is employed to ensure accurate dose measurement. The research utilized Cobalt-60 Teletherapy, which produces gamma radiation at energy levels of 1.17 MeV and 1.33 MeV, to assess the various field widths observed in PDD. In this experiment, the percentage depth dose (PDD) was evaluated by using a Farmer chamber, water phantom, PC electrometer, ionization chamber, computer software and barometer. The chamber was used throughout a range of field sizes, which varied from 5x5cm2 to 20x20cm2.The TRS-398 approach was employed to assess the radiation dose. Comparable findings were observed when conducting comparisons with published PDD data for cobalt-60 beams. The accumulation dose zone was found to be located approximately 0.5 cm below the surface, coinciding with the maximum (Zmax) dose site. The absorbed amount of radiation resulted in a decrease in the percentage depth dose (PDD) below the given depth. DOI: https://doi.org/10.52783/pst.643

A national-scale high-resolution runoff risk and channel network mapping workflow for diffuse pollution management

Managing diffuse pollution from agricultural land requires a spatially explicit risk assessment that can be applied over large areas. Major components of such assessments are the precise definition of both channel networks that often originate as small channels and streams, and Hydrologically Sensitive Areas (HSAs) of storm runoff that occur on land surfaces. Challenges relate to regions of complex topography and land use patterns, particularly those which have been heavily modified by arterial drainage. In this study, a national scale, transferrable workflow and analysis were developed using a specifically commissioned LiDAR survey. Research on the first half of Northern Ireland (6927 km2) is reported where field-edge drain to major river channels were mapped from 1 m (16 points per metre) digital terrain models, and in-field HSAs were defined across over 400,000 fields with a median field size of 0.86 ha. Manual drainage mapping supplemented with a novel automated drainage channel correction process resulted in an unparalleled high-resolution national drainage network with 37,320 km of channels, increasing mapped channel density from 0.9 km km−2 to 5.5 km km−2. The HSAs were based on a Soil Topographic Index (STI) system using hillslope and contributing area models combined with soil hydraulic characteristics. In all, 249 km2 of runoff risk HSAs were identified by extracting the top 95th percentile of the modelled STI as the areas with the highest propensity to generate in-field runoff. At field and individual farm scale these targeted risk maps of diffuse pollution were delivered to over 13,000 farmers and form part of the nationwide Soil Nutrient Health Scheme programme.