Demography and disorders of the French Bulldog population under primary veterinary care in the UK in 2013

Abstract Background Despite its Gallic name, the French Bulldog is a breed of both British and French origin that was first recognised by The Kennel Club in 1906. The French Bulldog has demonstrated recent rapid rises in Kennel Club registrations and is now (2017) the second most commonly registered pedigree breed in the UK. However, the breed has been reported to be predisposed to several disorders including ocular, respiratory, neurological and dermatological problems. The VetCompass™ Programme collates de-identified clinical data from primary-care veterinary practices in the UK for epidemiological research. Using VetCompass™ clinical data, this study aimed to characterise the demography and common disorders of the general population of French Bulldogs under veterinary care in the UK. Results French Bulldogs comprised 2228 (0.49%) of 445,557 study dogs under veterinary care during 2013. Annual proportional birth rates showed that the proportional ownership of French Bulldog puppies rose steeply from 0.02% of the annual birth cohort attending VetCompass™ practices in 2003 to 1.46% in 2013. The median age of the French Bulldogs overall was 1.3 years (IQR 0.6–2.5, range 0.0–13.0). The most common colours of French Bulldogs were brindle (solid or main) (32.36%) and fawn (solid or main) (29.9%). Of the 2228 French Bulldogs under veterinary care during 2013, 1612 (72.4%) had at least one disorder recorded. The most prevalent fine-level precision disorders recorded were otitis externa (14.0%, 95% CI: 12.6–15.5), diarrhoea (7.5%, 95% CI: 6.4–8.7), conjunctivitis (3.2%, 95% CI: 2.5–4.0), nails overlong (3.1%, 95% CI% 2.4–3.9) and skin fold dermatitis (3.0%, 95% CI% 2.3–3.8). The most prevalent disorder groups were cutaneous (17.9%, 95% CI: 16.3–19.6), enteropathy (16.7%, 95% CI: 15.2–18.3), aural (16.3%, 95% CI: 14.8–17.9), upper respiratory tract (12.7%, 95% CI: 11.3–14.1) and ophthalmological (10.5%, 95% CI: 9.3–11.9). Conclusions Ownership of French Bulldogs in the UK is rising steeply. This means that the disorder profiles reported in this study reflect a current young UK population and are likely to shift as this cohort ages. Otitis externa, diarrhoea and conjunctivitis were the most common disorders in French Bulldogs. Identification of health priorities based on VetCompass™ data can support evidence–based reforms to improve health and welfare within the breed

Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting

For person re-identification, existing deep networks often focus on representation learning. However, without transfer learning, the learned model is fixed as is, which is not adaptable for handling various unseen scenarios. In this paper, beyond representation learning, we consider how to formulate person image matching directly in deep feature maps. We treat image matching as finding local correspondences in feature maps, and construct query-adaptive convolution kernels on the fly to achieve local matching. In this way, the matching process and results are interpretable, and this explicit matching is more generalizable than representation features to unseen scenarios, such as unknown misalignments, pose or viewpoint changes. To facilitate end-to-end training of this architecture, we further build a class memory module to cache feature maps of the most recent samples of each class, so as to compute image matching losses for metric learning. Through direct cross-dataset evaluation, the proposed Query-Adaptive Convolution (QAConv) method gains large improvements over popular learning methods (about 10%+ mAP), and achieves comparable results to many transfer learning methods. Besides, a model-free temporal cooccurrence based score weighting method called TLift is proposed, which improves the performance to a further extent, achieving state-of-the-art results in cross-dataset person re-identification. Code is available at https://github.com/ShengcaiLiao/QAConv.Comment: This is the ECCV 2020 version, including the appendi

On Symbolic Ultrametrics, Cotree Representations, and Cograph Edge Decompositions and Partitions

Symbolic ultrametrics define edge-colored complete graphs K_n and yield a simple tree representation of K_n. We discuss, under which conditions this idea can be generalized to find a symbolic ultrametric that, in addition, distinguishes between edges and non-edges of arbitrary graphs G=(V,E) and thus, yielding a simple tree representation of G. We prove that such a symbolic ultrametric can only be defined for G if and only if G is a so-called cograph. A cograph is uniquely determined by a so-called cotree. As not all graphs are cographs, we ask, furthermore, what is the minimum number of cotrees needed to represent the topology of G. The latter problem is equivalent to find an optimal cograph edge k-decomposition {E_1,...,E_k} of E so that each subgraph (V,E_i) of G is a cograph. An upper bound for the integer k is derived and it is shown that determining whether a graph has a cograph 2-decomposition, resp., 2-partition is NP-complete

Realising biaxial reinforcement via orientation-induced anisotropic swelling in graphene-based elastomers

The biaxial mechanical properties constitute another remarkable advantage of graphene, but their evaluation has been overlooked in polymer nanocomposites. Herein, we provided an innovative and practical method to characterise biaxial reinforcement from graphene via swelling of elastomers, where graphene nanoplatelets were controlled to be oriented in-plane. The in-plane-aligned graphene imposed a biaxial constraining force to the elastomer during the swelling process that led to the anisotropic swelling behaviour of the bulk nanocomposites

On the Complex Network Structure of Musical Pieces: Analysis of Some Use Cases from Different Music Genres

This paper focuses on the modeling of musical melodies as networks. Notes of a melody can be treated as nodes of a network. Connections are created whenever notes are played in sequence. We analyze some main tracks coming from different music genres, with melodies played using different musical instruments. We find out that the considered networks are, in general, scale free networks and exhibit the small world property. We measure the main metrics and assess whether these networks can be considered as formed by sub-communities. Outcomes confirm that peculiar features of the tracks can be extracted from this analysis methodology. This approach can have an impact in several multimedia applications such as music didactics, multimedia entertainment, and digital music generation.Comment: accepted to Multimedia Tools and Applications, Springe

Tumor Suppression by RNA from C/EBPβ 3′UTR through the Inhibition of Protein Kinase Cε Activity

BACKGROUND: Since the end of last century, RNAs from the 3'untranslated region (3'UTR) of several eukaryotic mRNAs have been found to exert tumor suppression activity when introduced into malignant cells independent of their whole mRNAs. In this study, we sought to determine the molecular mechanism of the tumor suppression activity of a short RNA from 3'UTR of C/EBPβ mRΝΑ (C/EBPβ 3'UTR RNA) in human hepatocarcinoma cells SMMC-7721. METHODOLOGY/PRINCIPAL FINDINGS: By using Western blotting, immunocytochemistry, molecular beacon, confocal microscopy, protein kinase inhibitors and in vitro kinase assays, we found that, in the C/EBPβ 3'UTR-transfectant cells of SMMC-7721, the overexpressed C/EBPβ 3'UTR RNA induced reorganization of keratin 18 by binding to this keratin; that the C/EBPβ 3'UTR RNA also reduced phosphorylation and expression of keratin 18; and that the enzyme responsible for phosphorylating keratin 18 is protein kinase Cε. We then found that the C/EBPβ 3'UTR RNA directly inhibited the phosphorylating activity of protein kinase Cε; and that C/EBPβ 3'UTR RNA specifically bound with the protein kinase Cε-keratin 18 conjugate. CONCLUSION/SIGNIFICANCE: Together, these facts suggest that the tumor suppression in SMMC-7721 by C/EBPβ 3'UTR RNA is due to the inhibition of protein kinase Cε activity through direct physical interaction between C/EBPβ 3'UTR RNA and protein kinase Cε. These facts indicate that the 3'UTR of some eukaryotic mRNAs may function as regulators for genes other than their own

Multifunctional fabrics finished using electrosprayed hybrid Janus particles containing nanocatalysts

There is great market demand for fabrics equipped with multiple functionalities. However, most methods to impart these properties to a pristine fabric are complicated, time-consuming, and expensive. In this work, Janus particles with one side comprising TiO2 nanoparticles (NPs)-PVDF (poly (vinylidene fluoride)) and the other an epoxy resin (TPE) were deposited on a fabric surface. The aim was to endow the fabric with the superhydrophobic, UV resistance, and antimicrobial properties. The Janus particles were firmly attached to the fabrics through the adhesion effects of the epoxy resin. Characterization by XRD, SEM, EDX, and FTIR verified the successful finishing of the fabric with TPE particles. The ultraviolet protection factor increased from 7.86 for the pristine fabric to 733 after finishing. The finished fabric also exhibited superhydrophobic properties, with a water contact angle of 152°. Further, the coating of the fabric did not hamper its gas permeability. Potent antibacterial properties against E. coli were observed owing to the antibacterial properties of TiO2 under pre-irradiation by UV light. The protocols reported here provide a new platform for the nano-finishing of fabrics, allowing new functions to be imparted without compromising

The mechanics of reinforcement of polymers by graphene nanoplatelets

A detailed study has been undertaken of the mechanisms of stress transfer in polymeric matrices with different values of Young's modulus, Em, reinforced by graphene nanoplatelets (GNPs). For each material, the Young's modulus of the graphene filler, Ef, has been determined using the rule of mixtures and it is found to scale with the value of Em. Additionally stress-induced Raman bands shifts for the different polymer matrices show different levels of stress transfer from the polymer matrix to the GNPs, which again scale with Em. A theory has been developed to predict the stiffness of the bulk nanocomposites from the mechanics of stress transfer from the matrix to the GNP reinforcement based upon the shear-lag deformation of individual graphene nanoplatelets. Overall it is found that it is only possible to realise the theoretical Young's modulus of graphene of 1.05 TPa for discontinuous nanoplatelets as Em approaches 1 TPa; the effective modulus of the reinforcement will always be less for lower values of Em. For flexible polymeric matrices the level of reinforcement is independent of the graphene Young's modulus and, in general, the best reinforcement will be obtained in nanocomposites with strong graphene-polymer interfaces and aligned nanoplatelets with high aspect ratios