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Booming pet ownership in the UK and elsewhere brings significant implications for the carbon pawprint. Yet it is unlikely people will ever stop owning pets, so how can pet ownership be made more sustainable? At BVA Live, Justine Shotton and Jen Gale will explore the role of vets in this complex area and how they can support clients in minimising the impact of their pets on the planet., (© 2024 British Veterinary Association.)

Aims and Method: Our team of core and higher psychiatry trainees aimed to improve secondary mental health service detection of and response to gender-based violence (GBV) in South East London. We audited home treatment team (HTT), drug and alcohol (D&A) service and in-patient ward clinical records ( n = 90) for female and non-binary patients. We implemented brief, cost-neutral staff engagement and education interventions at service, borough and trust levels before re-auditing ( n = 86), completing a plan-do-study-act cycle., Results: Documented enquiry about exposure to GBV increased by 30% (HTT), 15% (ward) and 7% (D&A), post-intervention. We identified staff training needs and support for improving GBV care. Up to 56% of records identified psychiatric symptoms related to GBV exposure., Clinical Implications: Moves to make mental healthcare more trauma-informed rely on services first being supportive environments for enquiry, disclosure and response to traumatic stressors. Our collaborative approach across clinical services increased GBV enquiry and documentation. The quality of response is more difficult to measure and requires concerted attention.

Despite having a single evolutionary origin and conserved function, the mammalian placenta exhibits radical structural diversity. The evolutionary drivers and functional consequences of placental structural diversity are poorly understood. Humans and equids both display treelike placental villi, however these villi evolved independently and exhibit starkly different levels of invasiveness into maternal tissue (i.e. the number of maternal tissue layers between placental tissue and maternal blood). The villi in these species therefore serve as a compelling evolutionary case study to explore whether placentas have developed structural adaptations to respond to the challenge of reduced nutrient availability in less invasive placentas. Here, we use three-dimensional X-ray microfocus computed tomography and electron microscopy to quantitatively evaluate key structures involved in exchange in human and equid placental villi. We find that equid villi have a higher surface area to volume ratio and deeper trophoblastic vessel indentation than human villi. Using illustrative computational models, we propose that these structural adaptations have evolved in equids to boost nutrient transfer to compensate for reduced invasiveness into maternal tissue. We discuss these findings in relation to the 'maternal-fetal conflict hypothesis' of placental evolution.

We report the pathological and molecular findings in an adult male Himalayan red panda (Ailurus fulgens fulgens) whose death was attributed to parenchymal brain haemorrhage (PBH) of the thalamus. Post-mortem examination revealed severe, acute PBH and intraventricular haemorrhage with major involvement of the thalamus, as well as scattered chronic microinfarctions. Vascular disease in the brain and other organs was suggestive of systemic hypertension. Histological lesions included arteriolar hyalinosis and varying degrees of arteriosclerosis, arterial tunica media hypertrophy and hyperplasia and infiltration of arterial walls by lipid-laden macrophages. Other relevant findings included marked myocardial fibrosis, lymphoplasmacytic tubulointerstitial nephritis, lymphoplasmacytic meningoencephalitis and chronic mitral valve degeneration. The changes in the cerebral vasculature were consistent with hypertensive encephalopathy and a cerebrovascular accident, specifically PBH, which has not been previously reported in this species. Additionally, polymerase chain reaction analysis for red panda amdoparvovirus (RPAV) was positive in the brain and kidneys. Preceded by hypertensive vascular changes and brain microinfarctions, sudden death in this animal likely resulted from fatal PBH with intraventricular haemorrhage. The clinicopathological role of RPAV infection is unknown in this case, although its contribution to the chronic renal disease is considered possible in the context of our current understanding of RPAV-associated pathology., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

BVA's senior vice president Justine Shotton joined TV presenter Clare Balding on the sofa at Crufts to discuss a range of welfare issues, as part of Channel 4's coverage of the international dog show., (© 2023 British Veterinary Association.)

A 10.5-y-old intact female capybara ( Hydrochoerus hydrochaeris ) with a history of chronic weight loss was euthanized following discovery by palpation of a large intra-abdominal mass. Postmortem examination revealed a large, firm, tan mass expanding the uterine body and extensively adhered to the jejunum and abdominal wall. Numerous pinpoint to 3-cm diameter, tan-to-red, raised masses were present throughout the parietal peritoneum, liver, lungs, and intestinal serosa. Histologic examination of the uterine mass revealed well-differentiated smooth muscle intermixed with abundant collagen, interspersed with a highly anaplastic spindle cell population extending to the serosa; the masses in the lung, liver, and peritoneum were histologically very similar to the anaplastic uterine spindle cells. Immunohistochemical staining of the uterus and lung confirmed smooth muscle origin of the anaplastic cells. To our knowledge, leiomyosarcoma has not been reported previously in a capybara, and the widespread metastases in this case represent an unusually aggressive presentation of this rare malignancy. The animal also had an incidental dermal histiocytoma, a tumor that has also not been reported previously in this species, to our knowledge.

Hand pose estimation, formulated as an inverse problem, is typically optimized by an energy function over pose parameters using a 'black box' image generation procedure, knowing little about either the relationships between the parameters or the form of the energy function. In this paper, we show significant improvement upon such black box optimization by exploiting high-level knowledge of the parameter structure and using a local surrogate energy function. Our new framework, hierarchical sampling optimization (HSO), consists of a sequence of discriminative predictors organized into a kinematic hierarchy. Each predictor is conditioned on its ancestors, and generates a set of samples over a subset of the pose parameters, with only one selected by the highly-efficient surrogate energy. The selected partial poses are concatenated to generate a full-pose hypothesis. Repeating the same process, several hypotheses are generated and the full energy function selects the best result. Under the same kinematic hierarchy, two methods based on decision forest and convolutional neural network are proposed to generate the samples and two optimization methods are studied when optimizing these samples. Experimental evaluations on three publicly available datasets show that our method is particularly impressive in low-compute scenarios where it significantly outperforms all other state-of-the-art methods.

Zoos are required to maintain a high standard of animal welfare, and this can be assessed using a combination of resource-based and animal-based indices usually divided into behavioural indicators, physiological indicators and clinical/pathological signs. Modern animal welfare assessments should aim to encompass positive affective states and the indicators that are useful in assessing these are discussed. When developing factors to be scored for each species, there is huge variability in the available information about the natural biology for some zoo species and even less information concerning those animals in captivity. Wild baselines are not always the most accurate indicator of what is right for an animal in captivity, which makes the identification of factors to include within species-specific welfare assessment even more challenging. When planning a welfare strategy for any species, it is important that the full range of their biological requirements and needs are considered, but this can be challenging for some zoo species and it is not possible to define a “one size fits all” welfare strategy. The different approaches for welfare assessment are reviewed, including the development of the Animal Welfare Assessment Grid which offers an evidence-based tool for continual welfare assessment, using technology where appropriate, to facilitate decision making and lead to improvements in the animals’ quality of life.

Botswana has the second highest population of cheetah (Acinonyx jubatus) with most living outside protected areas. As a result, many cheetahs are found in farming areas which occasionally results in human-wildlife conflict. This study aimed to look at movement patterns of cheetahs in farming environments to determine whether cheetahs have adapted their movements in these human-dominated landscapes. We fitted high-time resolution GPS collars to cheetahs in the Ghanzi farmlands of Botswana. GPS locations were used to calculate home range sizes as well as number and duration of visits to landscape features using a time-based local convex hull method. Cheetahs had medium-sized home ranges compared to previously studied cheetah in similar farming environments. Results showed that cheetahs actively visited scent marking trees and avoided visiting homesteads. A slight preference for visiting game farms over cattle farms was found, but there was no difference in duration of visits between farm types. We conclude that cheetahs selected for areas that are important for their dietary and social needs and prefer to avoid human-occupied areas. Improved knowledge of how cheetahs use farmlands can allow farmers to make informed decisions when developing management practices and can be an important tool for reducing human-wildlife conflict., Competing Interests: The authors declare no competing or financial interests., (© 2017. Published by The Company of Biologists Ltd.)

Animals navigate their environment using a variety of senses and strategies. This multiplicity enables them to respond to different navigational requirements resulting from habitat, scale and purpose. One of the challenges social animals face is how to reunite after periods of separation. We explore a variety of possible mechanisms used to reunite the members of a cheetah coalition dispersed within a large area after prolonged separation. Using GPS data from three cheetahs reuniting after weeks of separation, we determined that 1) the likelihood of purely coincidental reunion is miniscule 2) the reunion occurred in an area not normally frequented 3) with very little time spent in the region in advance of the reunion. We therefore propose that timely encounter of scent markings where paths cross is the most likely mechanism used to aid the reunion., Competing Interests: The authors have declared that no competing interests exist.

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients-manually annotated by up to four raters-and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74%-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all sub-regions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.

Recovery from tracking failure is essential in any simultaneous localization and tracking system. In this context, we explore an efficient keyframe-based relocalization method based on frame encoding using randomized ferns. The method enables automatic discovery of keyframes through online harvesting in tracking mode, and fast retrieval of pose candidates in the case when tracking is lost. Frame encoding is achieved by applying simple binary feature tests which are stored in the nodes of an ensemble of randomized ferns. The concatenation of small block codes generated by each fern yields a global compact representation of camera frames. Based on those representations we define the frame dissimilarity as the block-wise hamming distance (BlockHD). Dissimilarities between an incoming query frame and a large set of keyframes can be efficiently evaluated by simply traversing the nodes of the ferns and counting image co-occurrences in corresponding code tables. In tracking mode, those dissimilarities decide whether a frame/pose pair is considered as a novel keyframe. For tracking recovery, poses of the most similar keyframes are retrieved and used for reinitialization of the tracking algorithm. The integration of our relocalization method into a hand-held KinectFusion system allows seamless continuation of mapping even when tracking is frequently lost.

Background and Objectives: The global architecture for providing development assistance for health (DAH) has become increasing complex in the last decade, with many new funding agencies entering the health sector. This study presents a detailed picture of European Union (EU) and EU member state originating DAH between 2006 and 2009; with a specific focus on assessing the extent of complementarity of development assistance sourced from the EU., Design: We use a combination of internal EU reporting systems, OECD-DAC creditor reporting system data and other data sources to estimate DAH flows. Our method uses a line by line project assessment in order to identify and categorise DAH flows., Results and Conclusions: Our findings show a complex picture of DAH flows--from source, to channel of assistance, to channel of implementation--that is hard to track at the global level, and rarely comprehensively and regularly tracked at the country level. While the majority of EU DAH is focused on low and lower middle income countries there also remains much disparity between countries; and further analysis is required to better understand whether these imbalances are fair and efficient; or result in overlap. We also recommend investment in quality control of DAH tracking internally within donor agencies, and investment in the development of country based systems in order to enable countries and development partners better harmonise DAH flows.

We describe two new approaches to human pose estimation. Both can quickly and accurately predict the 3D positions of body joints from a single depth image without using any temporal information. The key to both approaches is the use of a large, realistic, and highly varied synthetic set of training images. This allows us to learn models that are largely invariant to factors such as pose, body shape, field-of-view cropping, and clothing. Our first approach employs an intermediate body parts representation, designed so that an accurate per-pixel classification of the parts will localize the joints of the body. The second approach instead directly regresses the positions of body joints. By using simple depth pixel comparison features and parallelizable decision forests, both approaches can run super-real time on consumer hardware. Our evaluation investigates many aspects of our methods, and compares the approaches to each other and to the state of the art. Results on silhouettes suggest broader applicability to other imaging modalities.

With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers.

Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use as an off-the-shelf technology. This special issue is specifically dedicated to new algorithms and/or new applications based on the Kinect (or similar RGB-D) sensors. In total, we received over ninety submissions from more than twenty countries all around the world. The submissions cover a wide range of areas including object and scene classification, 3-D pose estimation, visual tracking, data fusion, human action/activity recognition, 3-D reconstruction, mobile robotics, and so on. After two rounds of review by at least two (mostly three) expert reviewers for each paper, the Guest Editors have selected twelve high-quality papers to be included in this highly popular special issue. The papers that comprise this issue are briefly summarized.

This paper proposes a novel method for recognizing faces degraded by blur using deblurring of facial images. The main issue is how to infer a Point Spread Function (PSF) representing the process of blur on faces. Inferring a PSF from a single facial image is an ill-posed problem. Our method uses learned prior information derived from a training set of blurred faces to make the problem more tractable. We construct a feature space such that blurred faces degraded by the same PSF are similar to one another. We learn statistical models that represent prior knowledge of predefined PSF sets in this feature space. A query image of unknown blur is compared with each model and the closest one is selected for PSF inference. The query image is deblurred using the PSF corresponding to that model and is thus ready for recognition. Experiments on a large face database (FERET) artificially degraded by focus or motion blur show that our method substantially improves the recognition performance compared to existing methods. We also demonstrate improved performance on real blurred images on the FRGC 1.0 face database. Furthermore, we show and explain how combining the proposed facial deblur inference with the local phase quantization (LPQ) method can further enhance the performance.

Computer vision has grown tremendously in the past two decades. Despite all efforts, existing attempts at matching parts of the human visual system's extraordinary ability to understand visual scenes lack either scope or power. By combining the advantages of general low-level generative models and powerful layer-based and hierarchical models, this work aims at being a first step toward richer, more flexible models of images. After comparing various types of restricted Boltzmann machines (RBMs) able to model continuous-valued data, we introduce our basic model, the masked RBM, which explicitly models occlusion boundaries in image patches by factoring the appearance of any patch region from its shape. We then propose a generative model of larger images using a field of such RBMs. Finally, we discuss how masked RBMs could be stacked to form a deep model able to generate more complicated structures and suitable for various tasks such as segmentation or object recognition.

This work addresses the challenging problem of simultaneously segmenting multiple anatomical structures in highly varied CT scans. We propose the entangled decision forest (EDF) as a new discriminative classifier which augments the state of the art decision forest, resulting in higher prediction accuracy and shortened decision time. Our main contribution is two-fold. First, we propose entangling the binary tests applied at each tree node in the forest, such that the test result can depend on the result of tests applied earlier in the same tree and at image points offset from the voxel to be classified. This is demonstrated to improve accuracy and capture long-range semantic context. Second, during training, we propose injecting randomness in a guided way, in which node feature types and parameters are randomly drawn from a learned (nonuniform) distribution. This further improves classification accuracy. We assess our probabilistic anatomy segmentation technique using a labeled database of CT image volumes of 250 different patients from various scan protocols and scanner vendors. In each volume, 12 anatomical structures have been manually segmented. The database comprises highly varied body shapes and sizes, a wide array of pathologies, scan resolutions, and diverse contrast agents. Quantitative comparisons with state of the art algorithms demonstrate both superior test accuracy and computational efficiency.

A new algorithm is presented for the automatic segmentation and classification of brain tissue from 3D MR scans. It uses discriminative Random Decision Forest classification and takes into account partial volume effects. This is combined with correction of intensities for the MR bias field, in conjunction with a learned model of spatial context, to achieve accurate voxel-wise classification. Our quantitative validation, carried out on existing labelled datasets, demonstrates improved results over the state of the art, especially for the cerebro-spinal fluid class which is the most difficult to label accurately.

During the past decade, several outbreaks of severe systemic disease associated with Feline calicivirus (FCV) have occurred in the USA and the UK. This new disease has caused high mortality in the affected animals and has been termed virulent systemic (VS)-FCV disease. Currently, there are no genetic or in vitro diagnostic methods to distinguish viruses isolated from cases of VS-FCV disease from other isolates. Here, five in vitro properties, as well as the capsid and proteinase-polymerase (pro-pol) sequences, of a set of FCV isolates that included seven isolates from five distinct VS-FCV outbreaks ('VS isolates') were investigated. Although all of the FCV isolates investigated had similar kinetics of growth under single-cycle conditions, VS isolates infected tissue-culture cells more efficiently under multiple-cycle growth conditions. Moreover, it was found that cells infected with VS isolates showed cytopathic effects earlier than cells infected with non-VS isolates, although no difference in relative ATP levels were noted at times when morphological changes were first seen. Both VS- and other (non-VS) isolates of FCV demonstrated similar temperature stabilities. Phylogenetic analyses and alignments of the capsid and pro-pol regions of the genome did not reveal any conserved changes that correlated with virulence, and the VS isolates did not segregate into a unique clade. These results suggest that VS isolates have arisen independently several times since first being described and can spread more efficiently in tissue culture than other isolates when infected at low multiplicity.

Nine patients with mesenchymal tumors of the skull base have undergone radical tumor excision by the use of the Infratemporal fossa approach. Three cases of chondrosarcoma, two of leiomyosarcoma, and one case each of synovial sarcoma, chondroid chordoma, myxoma, and fibromatosis were managed. In the mean postoperative review time of 6.6 years (range 1.7 to 13) there are no clinical or radiologic signs of recurrence at the primary site in any patient, although two have developed distant metastases. The purpose of this article is to demonstrate that, with aggressive and preferably early surgical management using this type of access to the skull base, complete removal of these tumors can be undertaken, and it is now possible to achieve permanent ablation of this type of pathologic condition at the skull base.

The infratemporal fossa approach to the skull base is an established method of treating neoplasms of this region. The type C variation has proved an effective means of removing adenoid cystic carcinoma invading the infratemporal fossa and skull base from the nasopharynx. A classification of these tumors is proposed, the surgical technique is described, and the results are given in this article.

The malignant Triton tumour is a malignant schwannoma with rhabdomyoblastic differentiation. This is the first report of this type of rare, aggressive sarcoma arising in the maxilla and only the third report of this type of pathology arising outside the context of von Recklinghausen's disease. Aspects of clinical and histopathological diagnosis are mentioned.

Leiomyosarcoma is a relatively uncommon soft tissue sarcoma usually presenting as a mass at the primary site. It arises in the retroperitoneal region, in the cutaneous or subcutaneous tissue of the extremities or, less commonly, from a large vein. A case is described where a patient presented with unilateral third, fourth, and sixth cranial, and ophthalmic division of trigeminal nerve palsies in whom biopsy of a longstanding lower limb mass demonstrated leiomyosarcoma. The presentation of this type of pathology has not been described previously.

Seventeen stab wounds to the cervical region presenting over a 3 year period are described. Clinical assessment, appropriate investigations and surgical management are discussed. Examination of the oral cavity for the presence of blood or displacement of the lateral oropharyngeal wall by an expanding haematoma, assessment of air bubbling from a wound, particularly on coughing, chest and lower cranial nerve examination are all required. Blind probing or attempted clamping of a bleeding vessel in a neck wound is not recommended. The use of urgent angiography in stab wounds high in the neck behind and above the angle of the mandible is recommended. Primary repair is optimal for all laryngotracheal, pharyngo-oesophageal and significant neurological injuries.