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Presentation attacks are becoming a serious threat to one of the most common biometric applications, namely face recognition (FR). In recent years, numerous methods have been presented to detect and identify these attacks using publicly available datasets. However, such datasets are often collected in controlled environments and are focused on one specific type of attack. We hypothesise that a model’s accurate performance on one or more public datasets does not necessarily guarantee generalisation across other, unseen face presentation attacks. To verify our hypothesis, in this paper, we present an experimental framework where the generalisation ability of pre-trained deep models is assessed using four popular and commonly used public datasets. Extensive experiments were carried out using various combinations of these datasets. Results show that, in some circumstances, a slight improvement in model performance can be achieved by combining different datasets for training purposes. However, even with a combination of public datasets, models still could not be trained to generalise to unseen attacks. Moreover, models could not necessarily generalise to a learned format of attack over different datasets. The work and results presented in this paper suggest that more diverse datasets are needed to drive this research as well as the need for devising new methods capable of extracting spoof-specific features which are independent of specific datasets.

Face Recognition is considered one of the most common biometric solutions these days and is widely used across a range of devices for various security purposes. The performance of FR systems has improved by orders of magnitude over the past decade. This is mainly due to the latest developments in computer vision and deep convolutional neural networks, and the availability of large training datasets. At the same time, these systems have been subject to various types of attacks. Presentation attacks are common, simple, and easy to implement. These simply involve presenting a video, photo, or mask to the camera or digital sensor and have proven capable of fooling FR systems and providing access to unauthorised users. Presentation attack detection is increasingly attracting more attention in the research community. A wide range of methods has already been developed to address this challenge. Deep learning-based methods in particular have shown very promising results. However, existing literature suggests that even with state-of-the-art methods, performance drops significantly in cross-dataset evaluation. We present a thorough, comprehensive, and technical review of existing literature on this timely and challenging problem. We first introduce and discuss the presentation attack problem and cover related and recent work in this area. In-depth technical details of existing presentation attack detection methods are then presented and critically discussed and evaluated, followed by a comprehensive discussion and evaluation of existing public datasets and commonly used evaluation metrics. Our review shows clearly that despite the recent and significant advances in this area of research, detecting unseen attacks is still considered a key problem. Machine learning methods tend to perform well, but only when test data comes from the same distribution as the training data (i.e. same dataset). New research directions are discussed in detail, including ways to improve the generalisation of machine learning methods, and move towards creating more stable presentation attack detection techniques that generalise across a wide range of unseen samples.

Advances in the CMOS process enables single-photon detection and timing to occur within an individual pixel. Pixel arrays incorporating this in-pixel timing methodology have been increasing in size, facilitating time of flight (ToF) imaging. This means that a fully parallel approach can be made to the collection of images, dramatically speeding up data collection in relation to sample scanning and allowing imaging based on time-correlated single-photon counting (TCSPC) to be made in real time. In this work we make use of a commercial TCSPC camera, based on an array of 192 × 126 imaging pixels with in-pixel timing applied in the area of time-domain near infrared spectroscopy. The potential of remote imaging using this methodology was demonstrated using two model systems. The effect of increasing scattering coefficient using a liquid based (milk added to water) system to assess real time potential was investigated. Additionally a more complex system consisting of a solid with liquid interior (egg) to verify the potential of remote imaging into the interior of the object with different illumination conditions was studied. Using a time-slicing approach intensity images related to each time bin in the ToF distribution were obtained and contrast between the yolk and albumin within the egg was observed.

The recent development in the areas of deep learning and deep convolutional neural networks has significantly progressed and advanced the field of computer vision (CV) and image analysis and understanding. Complex tasks such as classifying and segmenting medical images and localising and recognising objects of interest have become much less challenging. This progress has the potential of accelerating research and deployment of multitudes of medical applications that utilise CV. However, in reality, there are limited practical examples being physically deployed into front-line health facilities. In this paper, we examine the current state of the art in CV as applied to the medical domain. We discuss the main challenges in CV and intelligent data-driven medical applications and suggest future directions to accelerate research, development, and deployment of CV applications in health practices. First, we critically review existing literature in the CV domain that addresses complex vision tasks, including: medical image classification; shape and object recognition from images; and medical segmentation. Second, we present an in-depth discussion of the various challenges that are considered barriers to accelerating research, development, and deployment of intelligent CV methods in real-life medical applications and hospitals. Finally, we conclude by discussing future directions.

Video tampering methods have witnessed considerable progress in recent years. This is partly due to the rapid development of advanced deep learning methods, and also due to the large volume of video footage that is now in the public domain. Historically, convincing video tampering has been too labour intensive to achieve on a large scale. However, recent developments in deep learning-based methods have made it possible not only to produce convincing forged video but also to fully synthesize video content. Such advancements provide new means to improve visual content itself, but at the same time, they raise new challenges for state-of-the-art tampering detection methods. Video tampering detection has been an active field of research for some time, with periodic reviews of the subject. However, little attention has been paid to video tampering techniques themselves. This paper provides an objective and in-depth examination of current techniques related to digital video manipulation. We thoroughly examine their development, and show how current evaluation techniques provide opportunities for the advancement of video tampering detection. A critical and extensive review of photo-realistic video synthesis is provided with emphasis on deep learning-based methods. Existing tampered video datasets are also qualitatively reviewed and critically discussed. Finally, conclusions are drawn upon an exhaustive and thorough review of tampering methods with discussions of future research directions aimed at improving detection methods.

Video tampering detection remains an open problem in the field of digital media forensics. As video manipulation techniques advance, it becomes easier for tamperers to create convincing forgeries that can fool human eyes. Deep learning methods have already shown great promise in discovering effective features from data, particularly in the image domain; however, they are exceptionally data hungry. Labelled datasets of varied, state-of-the-art, tampered video which are large enough to facilitate machine learning do not exist and, moreover, may never exist while the field of digital video manipulation is advancing at such an unprecedented pace. Therefore, it is vital to develop techniques which can be trained on authentic or synthesised video but used to localise the patterns of manipulation within tampered videos. In this paper, we developed a framework for tampering detection which derives features from authentic content and utilises them to localise key frames and tampered regions in three publicly available tampered video datasets. We used convolutional neural networks to estimate quantisation parameter, deblock setting and intra/inter mode of pixel patches from an H.264/AVC sequence. Extensive evaluation suggests that these features can be used to aid localisation of tampered regions within video.

Face presentation attacks (PA) are a serious threat to face recognition (FR) applications. These attacks are easy to execute and difficult to detect. An attack can be carried out simply by presenting a video, photo, or mask to the camera. The literature shows that both modern, pre-trained, deep learning-based methods, and traditional hand-crafted, feature-engineered methods have been effective in detecting PAs. However, the question remains as to whether features learned in existing, deep neural networks sufficiently encompass traditional, low-level features in order to achieve optimal performance on PA detection tasks. In this paper, we present a simple feature-fusion method that integrates features extracted by using pre-trained, deep learning models with more traditional colour and texture features. Extensive experiments clearly show the benefit of enriching the feature space to improve detection rates by using three common public datasets, namely CASIA, Replay Attack, and SiW. This work opens future research to improve face presentation attack detection by exploring new characterizing features and fusion strategies.

Face recognition has recently become widespread in security applications. Although advancing technology has improved the performance of these systems, they are still prone to various attacks, including spoofing. The inherent feature extraction capability of machine learning techniques and deep neural networks has facilitated more accurate performance in spoofing detection. However, challenges still remain in the generalisation of these methods. One significant challenge is training dataset limitation in terms of size and variance. This paper investigates how different train/test ratios and variance in training data affect model performance with the NUAA dataset for spoofing detection. We show how using different splits of this dataset results in different models with different performances. We also open up new research directions by demonstrating how the problem of generalisation can be neatly demonstrated with an existing manageable dataset.

The presence of harmful algal bloom in many reservoirs around the world, alongside the lack of sanitation law/ordinance regarding cyanotoxin monitoring (particularly in developing countries), create a scenario in which the local population could potentially chronically consume cyanotoxin-contaminated waters. Therefore, it is crucial to develop low cost tools to detect possible systems failures and consequent toxin release inferred by morphological changes of cyanobacteria in the raw water. This paper aimed to look for the best combination of convolutional neural network (CNN), optimizer and image segmentation technique to differentiate P. agardhii trichomes before and after chemical stress caused by the addition of hydrogen peroxide. This method takes a step towards accurate monitoring of cyanobacteria in the field without the need for a mobile lab. After testing three different network architectures (AlexNet, 3ConvLayer and 2ConvLayer), four different optimizers (Adam, Adagrad, RMSProp and SDG) and five different image segmentations methods (Canny Edge Detection, Morphological Filter, HP filter, GrabCut and Watershed), the combination 2ConvLayer with Adam optimizer and GrabCut segmentation, provided the highest median accuracy (93.33%) for identifying H2O2-induced morphological changes in P. agardhii. Our results emphasize the fact that the trichome classification problem can be adequately tackled with a limited number of learned features due to the lack of complexity in micrographs from before and after chemical stress. To the authors' knowledge, this is the first time that CNNs were applied to detect morphological changes in cyanobacteria caused by chemical stress. Thus, it is a significant step forward in developing low cost tools based on image recognition, to shield water consumers, especially in the poorest regions, against cyanotoxin-contaminated water.

One of the key features of most document image digitisation systems is the capability of discerning between the main components of the printed representation at hand. In the case of engineering drawings, such as circuit diagrams, telephone exchanges or process diagrams, the three main shapes to be localised are the symbols, text and connectors. While most of the state of the art devotes to top-down recognition approaches which attempt to recognise these shapes based on their features and attributes, less work has been devoted to localising the actual pixels that constitute each shape, mostly because of the difficulty in obtaining a reliable source of training samples to classify each pixel individually. In this work, we present a convolutional neural network (CNN) capable of classifying each pixel, using a type of complex engineering drawings known as Piping and Instrumentation Diagram (P&ID) as a case study. To obtain the training patches, we have used a semi-automated heuristics-based tool which is capable of accurately detecting and producing the symbol, text and connector layers of a particular P&ID standard in a considerable amount of time (given the need of human interaction). Experimental validation shows that the CNN is capable of obtaining these three layers in a reduced time, with the pixel window size used to generate the training samples having a strong influence on the recognition rate achieved for the different shapes. Furthermore, we compare the average run time that both the heuristics-tool and the CNN need in order to produce the three layers for a single diagram, indicating future directions to increase accuracy for the CNN without compromising the speed.

Objectives The aim of this study was to evaluate a feline coronavirus (FCoV) reverse transcriptase quantitative PCR (RT-qPCR) on fine-needle aspirates (FNAs) from mesenteric lymph nodes (MLNs) collected in sterile saline for the purpose of diagnosing non-effusive feline infectious peritonitis (FIP) in cats. Methods First, the ability of the assay to detect viral RNA in MLN FNA preparations compared with MLN biopsy preparations was assessed in matched samples from eight cats. Second, a panel of MLN FNA samples was collected from a series of cats representing non-effusive FIP cases (n = 20), FCoV-seropositive individuals (n = 8) and FCoV-seronegative individuals (n = 18). Disease status of the animals was determined using a combination of gross pathology, histopathology and/or ‘FIP profile’, consisting of serology, clinical pathology and clinical signs. Results Viral RNA was detected in 18/20 non-effusive FIP cases; it was not detected in two cases that presented with neurological FIP. Samples from 18 seronegative non-FIP control cats and 7/8 samples from seropositive non-FIP control cats contained no detectable viral RNA. Thus, as a method for diagnosing non-effusive FIP, MLN FNA RT-qPCR had an overall sensitivity of 90.0% and specificity of 96.1%. Conclusions and relevance In cases with a high index of suspicion of disease, RT-qPCR targeting FCoV in MLN FNA can provide important information to support the ante-mortem diagnosis of non-effusive FIP. Importantly, viral RNA can be reliably detected in MLN FNA samples in saline submitted via the national mail service. When applied in combination with biochemistry, haematology and serological tests in cases with a high index of suspicion of disease, the results of this assay may be used to support a diagnosis of non-effusive FIP.

The following case report documents the investigation and progression of two cases of hepatic failure and hyperferraemia in Shetland ponies in Scotland exposed to high environmental levels of iron in groundwater, and to the authors’ knowledge describes the first use of deferoxamine in adult ponies. The importance of consideration of serum iron levels in cases of equine hepatic disease is highlighted and it is suggested that reduction in serum iron by phlebotomy or treatment with deferoxamine may be beneficial in cases displaying hyperferraemia.

AimsRisk assessment and management are crucial elements of clinical practice in mental health. Healthcare Improvement Scotland identified risk management as a key area for change, with risk tools identified as one necessary component. In NHS Greater Glasgow and Clyde (GG&C) the CRAFT tool replaced the Glasgow Risk Screen (GRS) in October 2019. The CRAFT tool is a 2 page document that comprises a broad risk screen, details of historical risk events and prompts for family and carer involvement. The aim of this study was to assess staff attitudes to the CRAFT, 12 months after it had been rolled out. Looking at whether the CRAFT tool is used to inform decision making about risk in clinical settings and if patients were involved in the risk management process.MethodAn electronic staff survey was distributed to all clinical staff within NHS GG&C Mental Health Services. Clinical staff includes the following professional groups: Medical, Nursing, Psychology, Occupational Therapists and Allied Health Professionals. Contact details were accessed via the relevant managers and surveys were sent via secure global address lists. Questions were focused around the following areas: time taken to complete/update/frequency of use/contact and ease of use, role in decision making, patient and carer involvement/knowledge, view on the impact of the CRAFT.ResultThere were 209 responses. This represents a response rate of approximately 10%. 89% of respondents had completed a CRAFT tool at some point but only 38% had received training. 15% reported that the CRAFT did not aid decision making about risk in clinical settings, whereas 37% said it did and 42% said it did sometimes. 46% report patients are consulted most of the time (34%) or always (12%). The qualitative impression was that the CRAFT was an improvement on its predecessor. However common themes from responders highlighted a lack of clinical relevance or impact decision making, lack of training in filling it out and cumbersome integration with the electronic case notes.ConclusionStaff perceptions of the CRAFT tool were generally negative with many feeling it was a box ticking exercise that had minimal real world impact on patient risk and its management. However many felt it was an improvement over the previous risk tool and the majority used it at some point to aid clinical decision making.

Objectives American political elites heatedly disagree over voter identification (ID) laws. Yet, the issue is not particularly polarizing at the mass level. Previous research mostly explores voter ID attitude correlates and how those policies shape turnout, but offers less insight into how average citizens understand the issue. We explore competing partisan frames on voter ID—voter fraud and voter suppression—that advance subtexts about partisan motivations and whom these laws benefit. Method We use an original nationally representative survey to examine how partisan motivated reasoning, strategic reasoning, and moral conviction influence voter ID frame perceptions and policy support among partisans. Results For average partisans, strategic reasoning and moral conviction significantly influence frame perceptions and voter ID attitudes, though not always along predicted party lines. Motivated reasoning proves inconsequential. Conclusions Republicans have won the “framing war” over voter ID, largely neutralizing the Democratic voter suppression frame, even among average Democrats.

There is a trend among academic libraries to increase collaboration between interlibrary loan and collection development to improve patron access to materials and build library collections. Instead of borrowing returnable materials, interlibrary loan may initiate purchases that will become part of the library's collection. This can mean anything from an organizational change combining interlibrary loan with the acquisitions unit or creating new workflows to facilitate purchasing. At the University of North Texas Libraries, the Interlibrary Loan office is a unit of the Access Services Department. Buying instead of borrowing for the ILL unit began with a Demand Driven Acquisitions (DDA) program and has expanded with the establishment of the University of North Texas Libraries' access-based collection development policy. Interlibrary Loan provides “Just-In-Time” (JIT) access to materials not available through regular interlibrary loan sources and adds relevant materials to the Libraries' collections.

Engineering drawings are common across different domains such as Oil & Gas, construction, mechanical and other domains. Automatic processing and analysis of these drawings is a challenging task. This is partly due to the complexity of these documents and also due to the lack of dataset availability in the public domain that can help push the research in this area. In this paper, we present a multiclass imbalanced dataset for the research community made of 2432 instances of engineering symbols. These symbols were extracted from a collection of complex engineering drawings known as Piping and Instrumentation Diagram (P&ID). By providing such dataset to the research community, we anticipate that this will help attract more attention to an important, yet overlooked industrial problem, and will also advance the research in such important and timely topics. We discuss the datasets characteristics in details, and we also show how Convolutional Neural Networks (CNNs) perform on such extremely imbalanced datasets. Finally, conclusions and future directions are discussed.

Though it is often a casual byproduct of social interactions, everyday political talk is nonetheless vital to deliberative democracy. In this chapter, we review current empirical research establishing the importance of everyday political talk. We also explore the psychology of everyday talk, explaining how over time everyday political talk encourages citizens to clarify their preferences, and develop understandings of politics that reflect their interests and identities. Finally, we probe the links between everyday talk, the media, and the formation of public opinion. Overall, we argue that by developing in citizens both a broad understanding of politics and a language to discuss it, everyday political talk prepares them for political action, including deliberation in more formal settings.

The University of North Texas Libraries provide extensive online access to academic journals through major vendor databases. As illustrated by interlibrary loan borrowing requests for items held in our databases, patrons often have difficulty navigating the available resources. In this study, the Interlibrary Loan staff used data gathered from the ILLiad interlibrary loan management system to investigate why patrons request locally available materials. This study resulted in recommendations for the Libraries' linking strategies in EBSCOhost databases. Several user education needs were identified and communicated to the Libraries' Subject Liaisons.

Based on social comparison and social identity theory, we argue that average partisans in contemporary U.S. politics view elections as group competitions in which partisan identities are at stake. Using nationally representative survey data, we demonstrate that stronger partisan identities, more than ideological identities or issue preferences, are associated with a greater sense of partisan hostility—specifically, party rivalry and anger. That hostility mediates the impact of partisan identities on political attitudes and actions. As a result, strong partisan identifiers hold the most hostile and uncivil attitudes and are the most likely to participate in elections. Thus, in the context of elections, the behavior of partisans resembles that of sports team members acting to preserve the status of their teams rather than thoughtful citizens participating in the political process for the broader good. We explore the implications of these findings for the current state of American politics.

Video tampering detection remains an open problem in the field of digital media forensics. Some existing methods focus on recompression detection because any changes made to the pixels of a video will require recompression of the complete stream. Recompression can be ascertained whenever there is a mismatch between compression parameters encoded in the syntax elements of the compressed bitstream and those derived from the pixels themselves. However, deriving compression parameters directly and solely from the pixels is not trivial. In this paper we propose a new method to estimate the H.264/AVC quantisation parameter (QP) in frame patches from raw pixels using Convolutional Neural Networks (CNN) and class composition. Extensive experiments show that QP of key-frames can be estimated using CNN. Results also show that accuracy drops for predicted frames. These results open new, interesting research directions in the domain of video tampering/forgery detection.

Talking and listening to political opponents is central to the proper functioning of deliberative democracy. But the social identity dynamics of partisan intergroup conflict make party identifiers in the US – Democrats and Republicans alike – less likely to engage in these activities. We argue that those group dynamics are gendered such that men are more sensitive than women to intergroup conflict and competition. Consequently, men are more likely to experience “intergroup anxiety” at the prospect of political interaction with partisan opponents. Using survey data from the 2010 Cooperative Congressional Election Study and experimental data, we found that men with higher intergroup anxiety were more likely than women to avoid cross-party political discussion, not listen when they did engage in such conversations, and reject information from outparty leaders. These results highlight the critical role that partisan social identities play in everyday democratic citizenship, but also emphasize the important an...

Summary Primary hyperparathyroidism was identified in a 17-year-old Arab × Welsh Pony mare that experienced weight loss for 6 months and was presented with mild facial asymmetry, right forelimb lameness and weight shifting amongst all limbs. Osteodystrophia fibrosa was demonstrated on radiographic examination of the head and there was radiographic evidence of osteopenia of the appendicular skeleton. The horse had persistent hypercalcaemia (4.0 mmol/l), hypophosphataemia (0.59 mmol/l) and an increased concentration of circulating parathyroid hormone (1401 pg/ml). On scintigraphic examination, a subjective focal increase in uptake of 99mtechnetium-sestamibi was identified in the right thyroid gland and at the thoracic inlet in delayed images. Surgical exploration of the thyroid region was unrewarding, whereas surgery at the thoracic inlet was not undertaken. One year later, the horse developed a pathological fracture of the third metacarpal bone and was subjected to euthanasia. At post mortem examination, a parathyroid adenoma was found at the level of the thoracic inlet adjacent to the trachea. Gross and histological examination also confirmed severe osteodystrophia fibrosa and osteopenia.

Polyneuropathies can have a variety of clinical presentations and tend to be rare in cats. In this report we describe a 6-year-old domestic shorthair cat with an acute and rapidly progressive onset of lower motor neuron and sensory signs affecting the spinal and cranial nerves. Histopathological examination revealed moderate-to-severe multifocal inflammatory infiltrates at the ventral and dorsal nerve roots, and dorsal spinal ganglia at the level of the L4 and cauda equina. The type and severity of inflammation varied between nerve roots, being composed of mainly neutrophils in some and mainly lymphocytes and macrophages in others. Immunohistochemistry showed a combination of neutrophils, macrophages and lymphocytes infiltrating the nerve roots and ganglia. The majority of the lymphocytes were T lymphocytes; only a few B lymphocytes were seen. Neurons within the affected ganglia showed central chromatolysis and necrosis. Wallerian-like degeneration and demyelination were observed in the nerve roots. A sensory and motor polyganglioradiculoneuritis was diagnosed. An autoimmune process similar to the acute motor and sensory neuropathy subtype of Guillain–Barré syndrome in humans or an infection by an unidentified agent were considered most likely.

Chronic spinal cord dysfunction occurs in dogs as a consequence of diverse aetiologies, including long-standing spinal cord compression and insidious neurodegenerative conditions. One such neurodegenerative condition is canine degenerative myelopathy (DM), which clinically is a challenge to differentiate from other chronic spinal cord conditions. Although the clinical diagnosis of DM can be strengthened by the identification of the Sod1 mutations that are observed in affected dogs, genetic analysis alone is insufficient to provide a definitive diagnosis. There is a requirement to identify biomarkers that can differentiate conditions with a similar clinical presentation, thus facilitating patient diagnostic and management strategies. A comparison of the cerebrospinal fluid (CSF) protein gel electrophoresis profile between idiopathic epilepsy (IE) and DM identified a protein band that was more prominent in DM. This band was subsequently found to contain a multifunctional protein clusterin (apolipoprotein J) that is protective against endoplasmic reticulum (ER) stress-mediated apoptosis, oxidative stress, and also serves as an extracellular chaperone influencing protein aggregation. Western blot analysis of CSF clusterin confirmed elevated levels in DM compared to IE (p

Practical relevance Osteoarthritis (OA) is very common, particularly in older cats, but its clinical significance has largely gone unrecognised until recently. As in other species, OA is often painful and appropriate treatment is required to improve the animal’s quality of life. Most cases appear to be primary or idiopathic. It is important for the clinician to actively seek these cases in the practice population. Clinical challenges The recognition of chronic arthritic pain is a major challenge since most cats will not exhibit lameness. The main features of feline OA are changes in behaviour and lifestyle, which develop gradually and which owners tend to interpret as simply being the effects of old age. A meaningful physical orthopaedic examination can be difficult to achieve. A lack of familiarity with feline joint radiographs, and the fact that major cartilage pathology can be present in the absence of any bony change, mean that radiographic identification of OA in the cat can also be problematic. Client questionnaire The recognition of chronic arthritic pain in the cat is based on owner questionnaires designed to elicit information about changes in mobility, activity levels, grooming habits and general demeanour. Evidence base Several publications now report on the significance of behavioural and lifestyle changes as indicators of chronic arthritic pain in the cat. However, there is not as yet a fully validated owner-based questionnaire for recognising chronic pain in the cat. Furthermore, the aetiopathogenesis of feline OA still requires detailed investigation. Such studies are likely to make a major contribution to comparative rheumatology, since feline OA, more so than the canine disease, shows many similarities with human OA.

A 12-year-old chinchilla ( Chinchilla lanigera) developed a slow-growing, soft, fluctuating, nonpainful mass on the ventral neck with focally extensive alopecia over a period of approximately 8 months. On postmortem examination, an extensive, multilobulated, cystic, neoplastic mass extended subcutaneously over the ventral and lateral neck with metastatic spread to submandibular lymph nodes, spleen, liver, and lungs. Neoplastic cells were strongly positive for vimentin and pan-cytokeratin but were negative for alpha–smooth muscle actin, S100, and myosin; no intracytoplasmic myofibrils were detected on phosphotungstic acid hematoxylin staining. Histologic and immunohistochemical examination of the mass led to a diagnosis of undifferentiated carcinoma of the salivary gland and contributes to the paucity of knowledge concerning neoplasia in chinchillas.

In democratic theory, the practice of discussing public affairs has been associated with desirable consequences for citizenship and democracy. We use Anglo-American survey data to examine twelve hypotheses about psychological foundations for four general conditions that such discussions might promote: autonomous citizens, political legitimacy, good representation and democratic communities. Our data combine detailed measures of public discussion with measures of more of its hypothesized civic consequences than have heretofore been available. They also enable us to probe, using specialized samples, causal inferences suggested by our analyses of random samples in our British and American communities. Six of the hypotheses are supported, including at least one regarding each of the four general liberal democratic conditions we investigate.

‘Everyday political talk’ is an increasingly important part of what Jane Mansbridge characterizes as ‘deliberative systems’ in industrialized democracies. However, how is it practiced by ordinary people? And how does their practice affect democracy and citizenship? Our paper addresses four questions: (1) How should everyday political talk be conceptualized as a component of the ‘deliberative system’? (2) What can and cannot be learned by studying normative topics like deliberation empirically? (3) How can we investigate such everyday talk using the methodologies of survey research, focus groups and content analysis? (4) What have we learned in our own research programs from each methodological approach?

It is a fundamental ideal of liberal democracy that all citizens should enjoy fully equal citizenship. Yet many minorities are still routinely ignored, excluded, patronized, and not regarded as full members of the political community. This denial of equal standing undermines their equal citizenship. Liberalism and Cultural Pluralism each advocate strategies to improve this situation. Their arguments build upon expectations about how citizens should, can, and do understand membership in the political community. Our survey and focus group data from six matched communities in the United States and Great Britain show how citizens’ understandings of membership in the political community incorporate communitarian attitudes that impede the liberal and cultural pluralist projects.

The University of Glasgow celebrated its 550th anniversaryin 2001, two years after the Faculty of Veterinary Medicinemarked its golden jubilee as part of the university, signify-ing the incorporation of the original Glasgow VeterinarySchool within a great civic institution. These events show-cased research advances and teaching innovations to stu-dents, as well as alumni and friends from all over the world.Students undertaking the five-year degree of Bachelor ofVeterinary Medicine and Surgery at Glasgow are based atGarscube Estate, four miles north of the main universitycampus, where the majority of learning and teaching activ-ity takes place. It accommodates an average of 100 studentsin each year. Although Glasgow is regarded as the only sin-gle-site veterinary school in the UK, the students also attendanimal husbandry management classes at Cochno Farm andResearch Centre, a 340-ha business enterprise that is locatedwithin five miles. The farm is quality assured for milk, beef,and lamb production and has 90 dairy cows and 550 ewesand lambs, as well as a number of beef cattle. The farm isalso used for clinical teaching in the final (fifth) year.The faculty was approved by the American VeterinaryMedical Association (AVMA) in 1999, currently one of onlyfour schools in Europe to have achieved this status, andrecently became the only center for the Clinical ProficiencyExamination outside North America, underlining the factthat we are preparing students for international venturesand collaboration. However, we also recognize at Glasgowthat clinical proficiency is insufficient alone to prepare stu-dents for global employment and that facilitating an under-standing of other cultures, languages, and environments isessential, as Gustafsson points out.

Objective—To evaluate 4 rapid supravital stains and 3 preparation techniques for use in the intraoperative diagnosis of intracranial lesions. Animals—10 dogs and 1 cat euthanatized for intracranial lesions. Procedure—Specimens were taken from lesions and slides prepared, using 3 techniques: touch impression, medium-pressure impression, or smear preparation. Preparations were then stained with 4 stains: modified Wright stain, May-Grünwald-Giemsa, toluidine blue, and zynostain and examined in a blinded randomized fashion. Cytologic diagnosis was compared with histopathologic diagnosis and classified on the basis of identification of the pathologic process and specific diagnosis into the following categories: complete correlation, partial correlation, or no correlation. Results—An overall diagnostic accuracy of 81% (107/132) was achieved on the basis of a combination of partial and complete correlation. Of the stains examined, modified Wright stain appeared to be most accurate, with complete correlation in 17 of 33 (52%) specimens and partial correlation in 12 of 33 (36%) specimens. Of the preparation methods, touch preparation and smear preparation provided the most accurate results, with an overall diagnostic accuracy of 82% (36/44) for both methods. However, smear preparations appeared to be of greater diagnostic value, with fewer nondiagnostic specimens, compared with touch preparations. Conclusions and Clinical Relevance—Cytologic preparations provide a useful diagnostic tool for the intraoperative diagnosis of intracranial lesions. All stains examined yielded promising results, the most accurate of which appeared to be the modified Wright stain. The smear preparation appeared to be the preparation method of greatest diagnostic value. (Am J Vet Res 2002;63:381–386)

Two adult guinea pigs were examined because they were lethargic and reluctant to walk. Additionally, I guinea pig had otitis media, and the other had dental malocclusion. Both guinea pigs had been fed a commercially available diet of cereals and pellets enriched with vitamin C and formulated for this species. Radiographically, the guinea pigs had coarse trabecular bone patterns, skeletal deformations, pathologic fractures, and polyarthritic degenerative joint disease. A double cortical line was also evident on several long bones, the pelvis, and the vertebrae. A diagnosis of osteopenia was confirmed by use of dual-energy x-ray absorptiometry. Analysis of a food sample fed to 1 guinea pig revealed calcium and phosphorus contents of 0.524 and 0.425%, respectively (Ca:P ratio, 1.23:1). Microscopic examination of bone tissue from both guinea pigs revealed severe fibrous osteodystrophy. Nutritional secondary hyperparathyroidism caused by calcium-phosphorus imbalance was considered to be the underlying cause of osteodystrophia fibrosa in both guinea pigs.

The concentration of serum alpha-tocopherol was measured in German shepherd dogs with chronic degenerative radiculomyopathy, and in German shepherd dogs and dogs of other breeds unaffected by the condition. The mean concentration was significantly higher in German shepherd dogs with the condition than in other breeds of dog unaffected by it, but it was not significantly higher than in unaffected German shepherd dogs. Estimates of components of variance indicated that the concentration varied more widely in individual affected dogs than in unaffected dogs, irrespective of breed. These results suggest that chronic degenerative radiculomyopathy in German shepherd dogs is unlikely to be due to uncomplicated vitamin E deficiency.

Primary T-cell lymphoma is a rare form of CNS neoplasia. Diagnosis may be aided by use of cytologic examination of CSF. Primary CNS T-cell lymphoma should be considered in a patient with multiple cranial nerve abnormalities, even if results of imaging studies are considered normal.

Most conceptual research on equality revolves around theoretical texts or legal theory and decisions, thus reflecting the thought of legal, political, or cultural elites. But in a democratic polity, we must attend to the political thought not just of politicos and academics, but ordinary citizens as well. In terms of its political significance, “What does equality mean” requires answering the question: what does equality mean to the mass public? We thus probe the meanings of “gender equality” in the public mind, using a unique set of questions included in the National Election Studies 1991 Pilot Study, and con-textualized within the literatures of feminist and legal theory and political psychology and public opinion. Most importantly, we distinguish among “empirical” and “normative” equality and discontent and among the domains of the polity, economy, and family; feature the problem of “equality” versus “sameness” and consider the relationship of these orientations to people's own structural circ...

The radiographic appearance of nodular fat necrosis is described in ten cats and one dog. The most common radiographic sign was the presence of a focal mineralized circular to oval soft tissue mass in the abdominal fat as present in 9 cats. These masses had a distinct eggshell-like rim encapsulating the lesion. In one cat and one dog multiple masses were present, without radiographic signs of mineralization. Abdominal ultrasound was performed in three cats and one dog, findings included the presence of hyperechoic masses with associated acoustic shadowing, some with a hypoechoic centre. Almost all animals were old and obese. In three cats and one dog, changes were confirmed with biopsy or post mortem examination. Lesions having the appearance of those in this paper are most likely incidental findings and should not be confused with abdominal masses of neoplastic origin. Ultrasound can be helpful in identifying such lesions.

The neuropathology of 20 German shepherd dogs and five German shepherd dog crosses with chronic degenerative radiculomyelopathy were analysed by conventional techniques, immunocytochemistry and electron microscopy. There were previously unrecognised changes in brain nuclei. In the spinal cord, both motor and sensory tracts were involved, principally in their more distal regions. Wallerian degeneration affected the corticorubrospinal pathways in the lateral columns and the ventral funiculi, predominantly in the caudal thoracic and lumbar segments, although more cranial involvement was also observed. The dorsal columns were affected in the caudal lumbar region and the cervical fasciculus gracilis. The regional distribution was variable between cases. Within the brain, abnormalities, including chromatolysis, gliosis and neuronal loss were observed in the red nucleus, lateral vestibular nucleus and, occasionally, in the dentate nucleus. The changes in brain nuclei were compared with those found in dogs at various times after a focal spinal injury. The neuronal changes in the brain may be related to the primary site of damage, and possible aetiological mechanisms are discussed.

Despite considerable research, the theory of gender difference in electoral behaviour remains underdeveloped, especially in accounting for variation across elections. We focus on two aspects requiring particular attention: (1) accounts of gender difference, especially distinguishing between positional explanations, in which gender differences stem from men and women taking the same considerations into account, but having different positions on those considerations, or structural explanations, in which gender differences stem from men and women taking different considerations into account in making judgements; (2) the effects of electoral context in cuing gender as a consideration, thus stimulating or inhibiting the appearance of gender differences. We use a case study of the 1992 US presidential election, often labelled ‘The Year of the Woman’, to explore these problems.

The investigation of protein dynamics has long been of interest, since protein interactions and functions can be determined by their structure and changes in conformation. Although fluorescence, occurring on the nanosecond timescale, from intrinsic fluorescent amino acids has been extensively used, in order to fully access conformational changes longer timescales are required. Phosphorescence enables processes on the microsecond to second timescale to be accessed. However, at room temperature this emission can be weak and non trivial to measure. It requires the removal of oxygen – a common triplet state quencher and appropriate instrumentation. In this work we make use of a chemical deoxygenator to study room temperature phosphorescence from tryptophan in human serum albumin excited using a pulsed UV light emitting diode. This is extended to monitor the phosphorescence emission upon increasing temperature, allowing pre-denaturing transitions to be observed. Time-resolved data are analysed, both as the sum of exponential decays and using a distribution analysis based on non extensive decay kinetics. These results are compared to a fluorescence study and both the average lifetime and contribution of the different emitting components were found to give more dramatic changes on the phosphorescence timescale.

Practical relevance Osteoarthritis (OA) is very common in the cat and in many cases is associated with significant long-term pain, which limits mobility and activity, and severely compromises the animal’s quality of life. Clinical challenges The treatment of chronic arthritic pain is a major challenge and many analgesic drugs used in other species are not licensed, not available or not tested for use in the cat. Many older cats with painful OA have some degree of chronic kidney disease (CKD) and many clinicians are reluctant to use non-steroidal anti-inflammatory drugs (NSAIDs) in these animals because of the potential for nephrotoxicity. Evidence base There are several publications that show that meloxicam is an effective NSAID for the cat and can be used long-term. It is easy to administer and there is published evidence that meloxicam can actually slow the progression of CKD in this species. Many other drugs are used to treat chronic pain in the cat but there is no documented evidence of their efficacy in OA. Unlike the dog, there is limited evidence for the effectiveness of omega-3 fatty acid-rich diets in managing feline OA and further work is required. There is no published data as yet for the usefulness or otherwise of nutraceuticals (glucosamine and chondroitin) in managing feline OA; studies in the authors’ clinic suggest some pain-relieving effect. Research into environmental enrichment as a way of improving quality of life in cats with painful OA is lacking, but it is an approach worth using where possible. Modifications to the environment (eg, provision of comfortable bedding and ramps) are also important.

Meningioangiomatosis is a rare proliferative disorder of the central nervous system. It occurs sporadically in dogs and is characterized by a leptomeningeal plaque that extends from the subarachnoid space along the perivascular spaces into the adjacent parenchyma. We describe the clinical presentation, magnetic resonance (MR) imaging and neuropathologic characteristics of two additional dogs with meningioangiomatosis, and document involvement of the thoracolumbar spinal cord, a site not previously described for this condition. MR imaging findings were different from those previously described, most likely reflecting the degree of vascularity and collagen deposition. The MR imaging features of meningioangiomatosis are not specific.

This study examines citizens' conceptions of rights, duties, and civic identities in the United States and Great Britain. By combining an information processing approach with a methodology--focus groups--that has seldom been used in political science, we have begun to explore empirical claims in contemporary theoretical controversies about citizenship. We find that in the minds of citizens citizenship is a complex matter, and that the roles constructed by citizens themselves blend together liberal and communitarian elements in ways unanticipated by many political theorists.