Approximate Location Research Articles

Nonsingular Indirect Boundary Element Method and Multistrategy Particle Swarm Optimization Algorithm Applied to 3D Subsurface Cavity Inversion

ABSTRACTThe inversion of subsurface geological structures is a crucial approach for gaining insights into the internal composition of the earth. In this paper, we propose a novel inversion method combining the nonsingular indirect boundary element method (IBEM) with the multistrategy particle swarm optimization (MSPSO) algorithm, tailored for accurately inverting 3D subsurface cavities. Leveraging the semi‐analytical nature of IBEM offers advantages such as dimensionality reduction, automatic fulfillment of radiation conditions at infinity, and high computational accuracy. Furthermore, to augment global optimization and local search capabilities, an MSPSO algorithm is introduced. Employing multiple optimization strategies enhances particle diversity, accelerates algorithm convergence, and mitigates the risk of local optima. Through the consideration of subsurface cavities with varying parameters, this method quickly identifies the approximate location of the cavity within a wide search range. The final results demonstrate that the proposed method can simultaneously and accurately invert the 3D spatial position, size, and orientation of the cavity.

Timing and geometry of the Chemehuevi Formation reveal a late Pleistocene sediment pulse into the Lower Colorado River

The Chemehuevi Formation is a distinctive 50−150-m-thick wedge-shaped Pleistocene sedimentary unit deposited by the Colorado River. It lines the perimeters of the river’s floodplains and bedrock canyons for more than 600 km between the mouth of the Grand Canyon and the delta region in the Gulf of California. The formation is composed of a basal tan to light-yellowish-brown and pale-orange mud-dominated facies overlain and interbedded by a light-yellow-brown sand-dominated facies. The unit is one of two extensively exposed aggradational packages in the Lower Colorado River corridor, in addition to a series of other smaller alluvial terrace deposits. The Chemehuevi Formation appears to represent the response of a fully integrated Colorado River system to a significant perturbation, in contrast to the Bullhead Alluvium, which is likely a unique result of Pliocene river integration. The aggradation of the Chemehuevi Formation in the Lower Colorado River corridor may be similarly due to a unique event in the Colorado River system, or it may instead be a well-preserved sedimentary sequence recording typical behavior of the Colorado River below the Grand Canyon in the late Pleistocene. As such, multiple causal mechanisms have been proposed, but no study to date has conclusively explained the Chemehuevi Formation. To help resolve its timing, duration, and origin, we applied post-infrared infrared stimulated luminescence, carbonate U-Th series, and zircon sensitive high-resolution ion microprobe U-Th series geochronology to determine the ages of key exposures of the unit over a wide spatial area. These new data demonstrate that the Chemehuevi Formation was deposited ca. 110−90 ka. The depositional ages collectively overlap, suggesting that deposition occurred rapidly relative to the resolution of the geochronometers. The new depositional timing coincides with a shift from glacial to interglacial conditions after the marine isotope stage 5-6 transition. This observation is consistent with a climate-induced sediment pulse as a causal mechanism, yet correlations with similar deposits in the Colorado River headwaters or in neighboring catchments appear elusive. Potentially, climate transitions between glacial and interglacial periods induced a sediment pulse from hillslopes of the Colorado River system that resulted in the Chemehuevi Formation. An alternative or additional explanation is that the Chemehuevi Formation represents release of lava dam−impounded sediment in the Grand Canyon. The surface geometry of the Chemehuevi Formation projects upstream to the approximate location of lava dams, and the largest possible lava dam impoundment (the Upper Prospect dam) is comparable in volume to the formation. The lava dam hypothesis appears to be a possible explanation for the Chemehuevi Formation. However, tying deposition to a specific lava dam or series of lava dams remains challenging due to discrepancies in timing and volume. The combined effects of a series of lava dams may have led to the Chemehuevi Formation, as the last Pleistocene lava dam eruption coincides with the onset of deposition. Alternatively, the formation may result from the combined effects of both regional climate transitions and the lava dams that created a transient reservoir to compound a climate transition−driven sediment pulse. The geochronologic data presented here do not allow us to distinguish between the lava dam or climate transition hypotheses but will need to be reconciled with any future proposed depositional model.

Mariette’s Newly Released Documents and the Chronology of the Apis Bulls

Summary The Louvre Museum recently placed online Mariette’s notebooks from the mid 19th century which include information on the find-spots of stelae from the Lesser Vaults of the Memphis Serapeum, the underground tomb complex of the Apis bulls at Saqqara. Some of these stelae name the reigning pharaoh and/or give dates for the bulls. The tombs had been ransacked but it seems that enough stelae remained close to their original positions to help determine the approximate location of each bull burial, a subject which has long been debated. Analysis of Mariette’s documents suggests a greater overlap between Dynasties 22 and 25 than is generally accepted.

Using an Ensemble of Segmentation Methods to Detect Vertebral Bodies on Radiographs.

Vertebral compression fractures may indicate osteoporosis but are underdiagnosed and underreported by radiologists. We have developed an ensemble of vertebral body (VB) segmentation models for lateral radiographs as a critical component of an automated, opportunistic screening tool. Our goal is to detect the approximate location of thoracic and lumbar VBs, including fractured vertebra, on lateral radiographs. The Osteoporotic Fractures in Men Study (MrOS) data set includes spine radiographs of 5994 men aged ≥65 years from 6 clinical centers. Two segmentation models, U-Net and Mask-RCNN (Region-based Convolutional Neural Network), were independently trained on the MrOS data set retrospectively, and an ensemble was created by combining them. Primary performance metrics for VB detection success included precision, recall, and F1 score for object detection on a held-out test set. Intersection over union (IoU) and Dice coefficient were also calculated as secondary metrics of performance for the test set. A separate external data set from a quaternary health care enterprise was acquired to test generalizability, comprising diagnostic clinical radiographs from men and women aged ≥65 years. The trained models achieved F1 score of U-Net = 83.42%, Mask-RCNN = 86.30%, and ensemble = 88.34% in detecting all VBs, and F1 score of U-Net = 87.88%, Mask-RCNN = 92.31%, and ensemble = 97.14% in detecting severely fractured vertebrae. The trained models achieved an average IoU per VB of 0.759 for U-Net and 0.709 for Mask-RCNN. The trained models achieved F1 score of U-Net = 81.11%, Mask-RCNN = 79.24%, and ensemble = 87.72% in detecting all VBs in the external data set. An ensemble model combining predictions from U-Net and Mask-RCNN resulted in the best performance in detecting VBs on lateral radiographs and generalized well to an external data set. This model could be a key component of a pipeline to detect fractures on all vertebrae in a radiograph in an automated, opportunistic screening tool under development.

The Particle of Haag's Local Quantum Physics: A Critical Assessment.

Rudolf Haag's Local Quantum Physics (LQP) is an alternative framework to conventional relativistic quantum field theory for combining special relativity and quantum theory based on first principles, making it of great interest for the purposes of conceptual analysis despite currently being relatively limited as a tool for making experimental predictions. In LQP, the elementary particles are defined as species of causal link between interaction events, together with which they comprise its most fundamental entities. This notion of particle has yet to be independently assessed as such. Here, it is captured via a set of propositions specifying particle characteristics and then compared to previous particle notions. Haag's particle differs decisively with respect to mechanical intuitions about particles by lacking, among other things, even an approximate independent space-time location. This notion is thus found to differ greatly even from those of relativistic quantum mechanics and quantum field theory, which have been applied to the known elementary particles.

CO2 emission heat map of Gulf Cooperation Council region using Python for Geographic Information Systems

Abstract As part of the efforts to ensure a place in the global competitive landscape, Oman is aligning itself with sustainable development through diversified economic measures. To address the United Nations thirteenth Sustainable Development Goal (SDG) which is climate action, the stakeholders of Oman need to understand the carbon dioxide (CO2) emissions and compare the amount of CO2 with the emissions in neighbouring Gulf Cooperation Council (GCC) countries such as United Arab Emirates (UAE), Bahrain, Qatar, Kuwait, and Kingdom of Saudi Arabia (KSA). In this research, an attempt is being made to collect the CO2 emission for all these countries and show them on a web map using python programming language. The data ranging from year 1964 to 2021 is collected from CO2 and Greenhouse Gas Emissions in Comma Separated Values (csv) format. For each country, an approximate location for Capital in terms of Latitude and Longitude is taken from google maps. Using folium library of python, these locations and CO2 emission for a particular year is plotted on google map Application Programming Interface (API). The findings reveal that Oman’s CO2 emissions from fossil fuels and industry in 2022 year is 72 million tonnes which is relatively lower when compared to those of smaller GCC countries such as Qatar (101 million tonnes) and the UAE (244 million tonnes). Nonetheless, a gradual upward trend of 12 million tonnes of CO2 emissions has been observed in Oman between the years 2019 to 2022. The python program provides an easy way to visualise the CO2 emission heatmap without the need of any proprietary software or program.

A fast numerical algorithm for finding all real solutions to a system of N nonlinear equations in a finite domain

AbstractA highly recurrent traditional bottleneck in applied mathematics, for which the most popular codes (Mathematica, Matlab, and Python as examples) do not offer a solution, is to find all the real solutions of a system of n nonlinear equations in a certain finite domain of the n-dimensional space of variables. We present two similar algorithms of minimum length and computational weight to solve this problem, in which one resembles a graphical tool of edge detection in an image extended to n dimensions. To do this, we discretize the n-dimensional space sector in which the solutions are sought. Once the discretized hypersurfaces (edges) defined by each nonlinear equation of the n-dimensional system have been identified in a single, simultaneous step, the coincidence of the hypersurfaces in each n-dimensional tile or cell containing at least one solution marks the approximate locations of all the hyperpoints that constitute the solutions. This makes the final Newton-Raphson step rapidly convergent to all the existent solutions in the predefined space sector with the desired degree of accuracy.

Automated crack identification in structures using acoustic waveforms and deep learning

Structural elements undergo multiple levels of damage at various locations due to environments and critical loading conditions. The level of damage and its location can be predicted using acoustic emission (AE) waveforms that are captured from the generation of inherent microcracks. Existing AE methods are reliant on the feature selection of the captured waveforms and may be subjective in nature. To automate this process, this paper proposes a deep-learning model to predict the damage severity and its expected location using AE waveforms. The model is based on a densely connected convolutional neural network (CNN) that offers superior feature extraction and minimal training data requirements. Time-domain AE waveforms are used as inputs of the proposed model to automate the process of predicting the severity of damage and identifying the expected location of the damage in structural elements. The proposed approach is validated using AE data collected from a concrete beam and a wooden beam and plate. The results show the capability of the proposed method for predicting the level of damage with an accuracy range of 92-95% and identifying the approximate location of damage with 90-100% accuracy. Thus, the proposed method serves as a robust technique for damage severity prediction and localization in civil structures.

The geography of avoided deforestation and sustainable forest management offsets: the enduring question of additionality

ABSTRACT Avoided deforestation and sustainable forest management (AD/SFM) offset projects have developed piecemeal, lacking consensus standards and receiving only quite low carbon prices. The diverse forces project developers face have led to a complex geography of different offsetting standards and funding sources adopted by various projects. Combining and updating existing AD/SFM pilot project databases, we produce – to our knowledge – the largest publicly available dataset of such projects’ approximate locations, containing nearly 800 worldwide. Using Cox proportional hazards models, we analyze the geography of these AD/SFM offset projects to understand better how different pressures project developers face in this weakly consolidated field have shaped where projects are more and less likely to be undertaken. We find that, at a fifty-kilometre-per-side hexagonal resolution, both AD/SFM projects tend to be located in areas with high above-ground biomass and high IUCN Red List species richness. Additionally, AD projects tend to be located in areas with stronger deforestation drivers. There is also a clear geographic specialization, with over 85% of the SFM projects in our dataset located in the United States. In contrast, AD projects have generally been established in countries that have engaged with the United Nations Reducing Emissions from Deforestation and Forest Degradation (UN-REDD) Programme or the World Bank’s Forest Carbon Partnership Facility. While AD/SFM projects may not be avoiding emissions at levels estimated in existing offset systems, they might still have a role to play in climate and habitat protection.

On the Homotopy-First Integral Method for Non-conservative Oscillators

This paper presents a ready-to-use formula for determining the number and approximate location of periodic orbits in second-order Lienard systems. As a result of the exact closed-form derived in [16], in which an ordinary differential equation (ODE) must be solved to determine the existence and location of periodic orbits for general non-conservative oscillators, a homotopy functional is defined for Lienard-type systems. This provides a closed-form and ready-to-use polynomial formula with roots as an approximation of the periodic orbit's amplitude. In addition, some examples are analyzed, along with conclusions and future plans.

GenTrajRec: A Graph-Enhanced Trajectory Recovery Model Based on Signaling Data

Signaling data are records of the interactions of users’ mobile phones with their nearest cellular stations, which could provide long-term and continuous-time location data of large-scale citizens, and therefore have great potential in intelligent transportation, smart cities, and urban sensing. However, utilizing the raw signaling data often suffers from two problems: (1) Low positioning accuracy. Since the signaling data only describes the interaction between the user and the mobile base station, they can only restore users’ approximate geographical location. (2) Poor data quality. Due to the limitations of mobile signals, user signaling may be missing and drifting. To address the above issues, we propose a graph-enhanced trajectory recovery network, GenTrajRec, to recover precise trajectories from signaling data. GenTrajRec encodes signaling data through spatiotemporal encoders and enhances the traveling semantics by constructing a signaling transition graph. In fusing the spatiotemporal information as well as the deep traveling semantics, GenTrajRec can well tackle the challenge of poor data quality, and recover precise trajectory from raw signaling data. Extensive experiments have been conducted on two real-world datasets from Mobile Signaling and Geolife, and the results confirm the effectiveness of our approach, and the positioning accuracy can be improved from 315 m per point to 82 m per point for signaling data using our network.

Combining video and GPS-tracking to study the spatial foraging distribution of a single-prey loading seabird

Seabirds are valuable indicators of marine ecosystem processes and studying seabird diets can shed light on natural or human-induced variability in food-web composition. Specifically single-prey loading seabird species such as terns have the potential to act as visual sentinels of prey availability offshore. However, obtaining diet information from remote bird colonies is often challenging and time consuming. In this pilot study we present a novel approach to combine two established methods to study seabird foraging ecology, providing a powerful and cost-effective tool to study the distribution of prey items available to seabirds. We combined GPS tracking data of Sandwich Terns (Thalasseus sandvicensis) with prey-observations from a hide in 2012 and 2013, and from semi-continuously recorded camera footage in 2017. By doing so, we identified 115 approximate catch locations of prey (86 herring/sprat Clupeidae, 29 sandeel Ammodytidae). Combining GPS-data and prey observations yielded detailed knowledge on the movements and chick diets of tracked birds as well as the spatial origin and lengths of captured prey items. Further catch distances of both Clupeidae and Ammodytidae resulted in deliveries of larger prey items and thus higher energy yield per trip, but also a higher energy expenditure per trip. We discuss the limitations and potential of our methodological approach to study foraging energetics during chick-provisioning of seabirds that carry prey items visible in their beaks.

A method for visualizing urban road events using distributed acoustic sensing

This study presents the construction of an urban underground sensing system using distributed acoustic sensing (DAS) technology, which utilizes the existing optical fiber infrastructure around urban roads for communication. To address the challenges posed by the complexity and variability of DAS data in infrastructure monitoring environments such as urban roads, as well as the difficulty and poor effectiveness of raw data visualization, a novel method for visualizing DAS data is proposed. This method involves preprocessing the data through wavelet threshold denoising, combining it with the root-mean-square (RMS) energy index to generate a visualization, and applying the dynamic threshold method to remove and suppress abnormal data indicators. Finally, this paper tested the visualization performance to assess the effectiveness of the proposed method in improving urban road safety management. The study focused on three typical urban road safety risk events: vehicle driving, construction, and road subsurface cavity incidents. The results demonstrate the efficacy of the data visualization method, showing improved visualization of vehicle trajectory directions and numbers, construction segment behaviors, and approximate road subsurface cavity locations in the time domain compared to the original data.

Poster 336: Reliability of Preoperative MRI in the Prediction of ACL Tear Type

Objectives: Anterior cruciate ligament (ACL) tears are among the most frequent ligament injuries in the United States. Most of these injuries are treated surgically, depending on patient-specific factors. Management of these injuries includes nonoperative management with stepwise rehabilitation or surgical treatment with ACL repair or reconstruction. Patient goals, a clinical evaluation, and preoperative MRI imaging are generally assessed to inform the choice of treatment. Classification of ACL tear-type based on stump morphology is critical to preoperative planning, as it can determine a patient’s eligibility for ACL preservation techniques. We aim to determine the efficacy of preoperative magnetic resonance imaging (MRI) in predicting ruptured ACL stump morphology and thus assist in preoperative planning and decision-making. Methods: This retrospective observational study utilized chart review from the case log of a single surgeon at an urban tertiary institution. The review identified patients who underwent the Bridge Enhanced ACL Repair (BEAR) procedure between January 1, 2022 and August 31, 2023. The inclusion criteria included patients who underwent a primary ACL repair with the BEAR technique and had adequate intraoperative and MRI images available for review. Patients excluded were those with inadequate intraoperative imaging or MRI imaging that was unavailable for review. For each patient included, the two senior authors assessed the morphology of the ACL stump on MRI (sagittal T2, coronal T2) and intraoperative arthroscopy images in a blinded manner and assigned a classification grade to each. The MRI-based morphology and the intraoperative image morphology of the tears were classified based on a system validated by DeFelice et al, which includes types 1 to 5 based on the location of the tear from most proximal to most distal. The correlation between the preoperative MRI assessment and the intraoperative arthroscopic assessment was interrogated using simple linear regression quantified with the Pearson correlation coefficient. Results: A total of 35 patients that underwent the BEAR procedure were identified. One patient was excluded due to inadequate intraoperative images. Of the remaining patients, 13 (38.2%) were male and 21 (61.8%) were female. The average patient age was 31, with a median age of 28. Most patients were injured while skiing (32.4%), while the second and third most prevalent mechanisms of injury were nonsports-related (23.4%) and soccer injuries (17.6%), respectively. Of the MRI tears that were analyzed, 9 (26.5%) were classified as type 1, 19 (55.9%) were type 2, and 5 (14.7%) were type 3. There were no tears identified as types 4 or 5 tears. Of the arthroscopic images that were analyzed, 21 (61.8%) were classified as type 1, 10 (29.4%) were type 2, 3 (8.8%) were type 3. Similarly, there were no tears identified as types 4 or 5. MRI accurately predicted the ACL tear type seen arthroscopically 55.9% (19/34) of the time. Of the (15) cases in which MRI did not correlate with the arthroscopic tear type, the MRI classification grade was within 1 grade of the arthroscopic grade 93.3% of the time (14/15). In the cases in which MRI was not correct in its grading, 93.3% of them (14/15) were classified as too high of a grade (MRI perceiving the tear to be more distal than it was in actuality). The Pearson correlation coefficient assessing the correlation between MRI identified tear type and arthroscopy identified tear type was 0.56. Conclusions: MRI accurately predicted the ACL tear type seen arthroscopically in only 55.9% of patients. In >90% of incorrect predictions, arthroscopy determined the ACL tear to be one classification more proximal than predicted by MRI. Our results demonstrate that while preoperative MRI can be useful in identifying approximate ACL tear location, it is essential to examine the ACL at time of arthroscopy for final determination of ACL stump size and viability for ACL restoration procedures. Moreover, a greater percentage of patients may be eligible for an ACL restoration procedure than predicted by preoperative MRI, highlighting the importance of discussing both ACL repair and ACL reconstruction with patients preoperatively. [Figure: see text]

Cortical Face-Selective Responses Emerge Early in Human Infancy.

In human adults, multiple cortical regions respond robustly to faces, including the occipital face area (OFA) and fusiform face area (FFA), implicated in face perception, and the superior temporal sulcus (STS) and medial prefrontal cortex (MPFC), implicated in higher-level social functions. When in development, does face selectivity arise in each of these regions? Here, we combined two awake infant functional magnetic resonance imaging (fMRI) datasets to create a sample size twice the size of previous reports (n = 65 infants; 2.6-9.6 months). Infants watched movies of faces, bodies, objects, and scenes, while fMRI data were collected. Despite variable amounts of data from each infant, individual subject whole-brain activation maps revealed responses to faces compared to nonface visual categories in the approximate location of OFA, FFA, STS, and MPFC. To determine the strength and nature of face selectivity in these regions, we used cross-validated functional region of interest analyses. Across this larger sample size, face responses in OFA, FFA, STS, and MPFC were significantly greater than responses to bodies, objects, and scenes. Even the youngest infants (2-5 months) showed significantly face-selective responses in FFA, STS, and MPFC, but not OFA. These results demonstrate that face selectivity is present in multiple cortical regions within months of birth, providing powerful constraints on theories of cortical development.

Dissecting heritability, environmental risk, and air pollution causal effects using > 50 million individuals in MarketScan

Large national-level electronic health record (EHR) datasets offer new opportunities for disentangling the role of genes and environment through deep phenotype information and approximate pedigree structures. Here we use the approximate geographical locations of patients as a proxy for spatially correlated community-level environmental risk factors. We develop a spatial mixed linear effect (SMILE) model that incorporates both genetics and environmental contribution. We extract EHR and geographical locations from 257,620 nuclear families and compile 1083 disease outcome measurements from the MarketScan dataset. We augment the EHR with publicly available environmental data, including levels of particulate matter 2.5 (PM2.5), nitrogen dioxide (NO2), climate, and sociodemographic data. We refine the estimates of genetic heritability and quantify community-level environmental contributions. We also use wind speed and direction as instrumental variables to assess the causal effects of air pollution. In total, we find PM2.5 or NO2 have statistically significant causal effects on 135 diseases, including respiratory, musculoskeletal, digestive, metabolic, and sleep disorders, where PM2.5 and NO2 tend to affect biologically distinct disease categories. These analyses showcase several robust strategies for jointly modeling genetic and environmental effects on disease risk using large EHR datasets and will benefit upcoming biobank studies in the era of precision medicine.

Approximate vs. precise location in popular location-based services

ABSTRACT Location-based services can provide many benefits to their users but sharing one’s location with third parties also incurs privacy risks. As one way to mitigate this, the two major mobile operating systems provide an approximate location feature, which enables users to only share their approximate location instead of their precise location. In order to assess the usefulness of this feature in practice, we analysed 36 iOS and 36 Android apps regarding the impact of using approximate location had on the functionality and usability in practical use. To achieve this, we used each app following a structured methodology with both precise and approximate location and recorded differences in app behaviour. Our results show that using approximate location caused many of the apps’ functionalities to stop working, although some functionalities were more affected than others. We also observed differences regarding which functionalities were most affected and which operating system the app was running on. Our results shed light on the practical use of approximate location in common apps and can benefit researchers interested in location privacy and app use.

AidData’s Geospatial Global Chinese Development Finance Dataset

AidData’s Global Chinese Development Finance Dataset (Version 3.0) provides detailed information about more than 20,000 development projects across 165 low- and middle-income countries financed by 791 official sector Chinese donors and lenders from 2000 to 2021. In this study, we introduce a methodology for identifying the geospatial features of these projects. Our application of the methodology has resulted in the Geospatial Global Chinese Development Finance Dataset (Version 3.0), which captures the geospatial features of 9,405 projects across 148 low- and middle-income countries supported by Chinese grant and loan commitments worth more than USD 830 billion. The dataset provides details for 6,266 projects containing spatial definitions of roads, railways, power plants, transmission lines, buildings, and other precisely geocoded features. It identifies approximate and administrative-level locations for 3,139 additional projects. The methodology, dataset, and the code used to construct the dataset have been made publicly available to facilitate replication and future applications.

Effect of ICCP on tensile performance and piezoresistive effect of CFRCM plates

Currently, extensive research has been conducted on carbon fabric−reinforced cementitious matrix (CFRCM) composites, impressed current cathodic protection (ICCP), and the piezoresistive effect in the field of strengthening of reinforced concrete (RC) structures, corrosion protection of steel reinforcement, and structural health monitoring, respectively. This study utilized two types of matrix materials: normal matrix (sand conforming to ISO standard) and seawater sea-sand matrix. The mechanism by which the ICCP procedure affects the degradation of tensile performance in CFRCM plates with these two types of matrix materials was investigated in the study. Additionally, the piezoresistive effects of CFRCM with the two types of matrix materials after the ICCP procedure were analyzed, and the impact of ICCP on the piezoresistive effect was also investigated. By observing the piezoresistive effect of each CFRCM segment, the sequence of crack propagation and an approximate crack location can be inferred. Finally, the tensile performance of CFRCM with charge density was investigated. Leveraging the dual functionality of carbon fiber reinforcement and sensing, this study lays the groundwork for the development of a triple-functional system encompassing impressed current cathodic protection, structural strengthening, and structural health monitoring (ICCP-SS-SHM). Seawater sea-sand has the potential to be used as an alternative to freshwater river sand, which is beneficial for addressing the shortage of freshwater river sand resources.

Small-scale sheep and cattle enterprises in Scotland: Demographics, animal health, and biosecurity

Livestock keepers who operate on a small scale in the United Kingdom are often described as either smallholders or hobby farmers; however, this is not always the case. There is another distinct population in Scotland. The crofting system promotes the preservation of a way of life that is significant to the cultural heritage of Scotland, whilst at the same time utilising and maintaining marginal land that could otherwise be deemed of very low productive value. We developed two cross-sectional questionnaire surveys to gather descriptive data about individuals from two populations (crofters and smallholders) who kept sheep and/or cattle. Our aim was to explore demographics, animal health, husbandry, and biosecurity practices of these two communities, including how they may interact with other livestock sectors. Most respondents in each population kept sheep, with far fewer keeping cattle. There was a distinct geographical difference in the approximate location of respondents’ holdings. Movement of sheep was often local, temporary, and exempt from reporting to national databases. Visits from the vet were infrequent, but the vet remained an important source of animal health advice, alongside peer networks. The information from these surveys is valuable because policy decisions taken with predominantly larger, commercial-scale enterprises in mind also frequently apply to small-scale enterprises, even though these smaller enterprises may not have the same opportunity to influence those decisions or implement the requirements. Aspects of agricultural activity and food production at the scale explored in these surveys – including plurality of employment and diversification away from purely agricultural activities – are relevant to the United Nations Sustainable Development Goals of sustainable cities and communities, zero hunger and life on land. In this context, competent authorities should support this type of context-sensitive agriculture, alongside seeking to maintain animal health and welfare standards at the highest possible level on a national scale. Our surveys contribute to improved understanding of how these enterprises function and therefore will support policy makers when considering the breadth of keepers and circumstances affected by rules and regulations governing agriculture.