37 research outputs found
Prediction of crack propagation and arrest in X100 natural gas transmission pipelines with the strain rate dependent damage model (SRDD). Part 1:A novel specimen for the measurement of high strain rate fracture properties and validation of the SRDD model parameters
Brainstem phaeohyphomycosis due to Curvularia lunata (Cochliobolus lunatus) in a cat
A 13-year-old female neutered domestic short-hair cat was presented with chronic progressive vestibular ataxia, lethargy and anorexia. Clinical examination revealed bilateral mucopurulent nasal discharge. Neurological examination revealed obtundation, a right head tilt, ambulatory tetraparesis, generalised vestibular ataxia, decreased postural reactions in all limbs, right Horner's syndrome, spontaneous conjugate jerk rotatory nystagmus and right positional ventral strabismus. Neuroanatomical localisation was observed in the right central vestibular system. Computed tomography revealed a solitary ill-defined contrast-enhancing mass lesion at the level of the right cerebellopontine angle. Cerebrospinal fluid (CSF) analysis revealed mild mononuclear pleocytosis and fungal elements. CSF culture was positive for Curvularia spp. Further tests for underlying diseases were all negative. The cat was treated with antibiotic and antifungal treatment, but it deteriorated rapidly and was euthanased. Necropsy of the brainstem mass lesion revealed pyogranulomatous inflammation. Panfungal polymerase chain reaction (PCR) targeting the internal transcribed spacer (ITS) region and subsequent sequencing identified Curvularia lunata in the formalin fixed brain tissue. This is the first report of brainstem phaeohyphomycosis by Curvularia lunata (Pleosporales) in a cat. In addition, this is the first report among animal and humans where fungal elements of Curvularia lunata were found in the CSF cytology. Opportunistic fungal pathogens should be always considered within the differential diagnoses list in cats with neurological signs and advanced imaging findings compatible with solitary mass lesions in the brain. In feline patients with pyogranulomatous meningoencephalitis and a suspicion of a fungal aetiology, panfungal PCR for the ITS region and sequencing should be performed regardless of the absence of fungal elements in histopathology
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Graphene-based strain sensing in composites for structural and health monitoring applications
Copyright © 2022 The Author(s). Composite structures are attracting more interest due to their outstanding mechanical properties; thus, their inspection and health assessment are key items for their safe use. In this article we present a graphene-based sensor that evaluates the strain generated within a composite. A finite element model was developed to investigate the mechanism driving the graphene to act as a strain sensor. A prototype sensor was manufactured, using a commercially available graphene ink. The strain in composite samples was measured and the gauge factor identified by applying different load scenarios. The graphene sensor proved to be able to evaluate strain at various levels providing a gauge factor (exceeding 6) higher than commercially available strain gauges.Innovate UK for the project GRAPHOSITE “A Graphene Sensor for Defect Detection and Predictive Maintenance in Composite Materials” [grant number 104266]
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A dimensional approach to modeling symptoms of neuropsychiatric disorders in the marmoset monkey.
Some patients suffering from the same neuropsychiatric disorder may have no overlapping symptoms whilst others may share symptoms common to other distinct disorders. Therefore, the Research Domain Criteria initiative recognises the need for better characterisation of the individual symptoms on which to focus symptom-based treatment strategies. Many of the disorders involve dysfunction within the prefrontal cortex (PFC) and so the marmoset, due to their highly developed PFC and small size, is an ideal species for studying the neurobiological basis of the behavioural dimensions that underlie these symptoms.Here we focus on a battery of tests that address dysfunction spanning the cognitive (cognitive inflexibility and working memory), negative valence (fear generalisation and negative bias) and positive valence (anhedonia) systems pertinent for understanding disorders such as ADHD, Schizophrenia, Anxiety, Depression and OCD. Parsing the separable prefrontal and striatal circuits and identifying the selective neurochemical modulation (serotonin vs dopamine) that underlie cognitive dysfunction have revealed counterparts in the clinical domain. Aspects of the negative valence system have been explored both at individual- (trait anxiety and genetic variation in serotonin transporter) and circuit-based levels enabling the understanding of generalisation processes, negative biases and differential responsiveness to SSRIs. Within the positive valence system, the combination of cardiovascular and behavioural measures provides a framework for understanding motivational, anticipatory and consummatory aspects of anhedonia and their neurobiological mechanisms. Together, the direct comparison of experimental findings in marmosets with clinical studies is proving an excellent translational model to address the behavioural dimensions and neurobiology of neuropsychiatric symptoms. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 328-353, 2017.This work was supported by long term funding from the MRC (ACR) and the Wellcome Trust (TWR) and was performed within the Behavioural and Clinical Neuroscience Institute, University of Cambridge, funded jointly by the Wellcome Trust and MRC. LO is supported by an MRC studentship.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/dneu.2244
Unpublished Mediterranean and Black Sea records of marine alien, cryptogenic, and neonative species
To enrich spatio-temporal information on the distribution of alien, cryptogenic, and neonative species in the Mediterranean and the Black Sea, a collective effort by 173 marine scientists was made to provide unpublished records and make them open access to the scientific community. Through this effort, we collected and harmonized
a dataset of 12,649 records. It includes 247 taxa, of which 217 are Animalia, 25 Plantae and 5 Chromista, from 23 countries surrounding the Mediterranean and the Black Sea. Chordata was the most abundant taxonomic group, followed by Arthropoda, Mollusca, and Annelida. In terms of species records, Siganus luridus, Siganus rivulatus,
Saurida lessepsianus, Pterois miles, Upeneus moluccensis, Charybdis (Archias) longicollis, and Caulerpa cylindracea were the most numerous. The temporal distribution of the records ranges from 1973 to 2022, with 44% of the records in 2020–2021. Lethrinus borbonicus is reported for the first time in the Mediterranean Sea, while Pomatoschistus quagga, Caulerpa cylindracea, Grateloupia turuturu, and Misophria pallida are first records for the Black Sea; Kapraunia schneideri is recorded for the second time in the Mediterranean and for the first time in Israel; Prionospio depauperata and Pseudonereis anomala are reported for the first time from the Sea of Marmara. Many first country records are also included, namely: Amathia verticillata (Montenegro), Ampithoe valida (Italy), Antithamnion amphigeneum (Greece), Clavelina oblonga (Tunisia and Slovenia), Dendostrea cf. folium (Syria), Epinephelus fasciatus (Tunisia), Ganonema farinosum (Montenegro), Macrorhynchia philippina (Tunisia), Marenzelleria neglecta (Romania), Paratapes
textilis (Tunisia), and Botrylloides diegensis (Tunisia)
Degradation of organic pollutants and characteristics of activated sludge in an anaerobic/anoxic/oxic reactor treating chemical industrial wastewater
Sign Language Recognition
This chapter covers the key aspects of sign-language recognition (SLR), starting with a brief introduction to the motivations and requirements, followed by a précis of sign linguistics and their impact on the field. The types of data available and the relative merits are explored allowing examination of the features which can be extracted. Classifying the manual aspects of sign (similar to gestures) is then discussed from a tracking and non-tracking viewpoint before summarising some of the approaches to the non-manual aspects of sign languages. Methods for combining the sign classification results into full SLR are given showing the progression towards speech recognition techniques and the further adaptations required for the sign specific case. Finally the current frontiers are discussed and the recent research presented. This covers the task of continuous sign recognition, the work towards true signer independence, how to effectively combine the different modalities of sign, making use of the current linguistic research and adapting to larger more noisy data set