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

Motion Capture of Hands in Action Using Discriminative Salient Points

Abstract. Capturing the motion of two hands interacting with an object is a very challenging task due to the large number of degrees of freedom, self-occlusions, and similarity between the fingers, even in the case of multiple cameras observing the scene. In this paper we propose to use discriminatively learned salient points on the fingers and to estimate the finger-salient point associations simultaneously with the estimation of the hand pose. We introduce a differentiable objective function that also takes edges, optical flow and collisions into account. Our qualitative and quantitative evaluations show that the proposed approach achieves very accurate results for several challenging sequences containing hands and objects in action.

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)

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

Offline Trace Synchronization for Smartphone Energy Profiling

Energy profiling is a means to effectively understand the power behavior of smartphone applications. However, no tool that effectively combines portability, accuracy and automation has been proposed yet. In this thesis a new approach is proposed, which sets the basis for such a tool by solving a trace synchronization problem. TRAce Merger uses the event trace from a mobile device and the power trace from a measurement device. It synchronizes them offline, maps the mobile device events trace on the corresponding trace from the power measurement tool, and attributes energy consumption to smartphone functionalities. The event and power traces traces from these two systems contain timestamps based on the corresponding local clocks. Taking the aforementioned clocks inaccuracy and deviation into account, we synchronize these traces to extract useful information from their contents. We achieved energy consumption attribution to smartphone functionalities by solving this synchronization problem with milliseconds accuracy.Computer EngineeringSoftware TechnologyElectrical Engineering, Mathematics and Computer Scienc