Forehead Skin Blood Flow in Normal Neonates during Active and Quiet Sleep, Measured with a Diode Laser Doppler Instrument

Changes in forehead skin blood flow during active and quiet sleep were determined in 16 healthy neonates using a recently developed semi-conductor laser Doppler flow meter without light conducting fibres. Measurements were carried out at a postnatal age varying from 5 hours to 7 days. The two sleep states could be distinguished in 17 recordings. The mean skin blood flow values during active sleep were significantly higher (p<0.01) than those during quiet sleep, the mean increase being 28.1%. The variability of the flow signal, expressed as the coefficient of variation, changed significantly from 23.1% during active sleep to 18.2% during quiet sleep

Music SketchNet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm

Drawing an analogy with automatic image completion systems, we propose Music SketchNet, a neural network framework that allows users to specify partial musical ideas guiding automatic music generation. We focus on generating the missing measures in incomplete monophonic musical pieces, conditioned on surrounding context, and optionally guided by user-specified pitch and rhythm snippets. First, we introduce SketchVAE, a novel variational autoencoder that explicitly factorizes rhythm and pitch contour to form the basis of our proposed model. Then we introduce two discriminative architectures, SketchInpainter and SketchConnector, that in conjunction perform the guided music completion, filling in representations for the missing measures conditioned on surrounding context and user-specified snippets. We evaluate SketchNet on a standard dataset of Irish folk music and compare with models from recent works. When used for music completion, our approach outperforms the state-of-the-art both in terms of objective metrics and subjective listening tests. Finally, we demonstrate that our model can successfully incorporate user-specified snippets during the generation process.Comment: 8 pages, 8 figures, Proceedings of the 21st International Society for Music Information Retrieval Conference, ISMIR 202

Multitrack Music Transformer: Learning Long-Term Dependencies in Music with Diverse Instruments

Existing approaches for generating multitrack music with transformer models have been limited to either a small set of instruments or short music segments. This is partly due to the memory requirements of the lengthy input sequences necessitated by existing representations for multitrack music. In this work, we propose a compact representation that allows a diverse set of instruments while keeping a short sequence length. Using our proposed representation, we present the Multitrack Music Transformer (MTMT) for learning long-term dependencies in multitrack music. In a subjective listening test, our proposed model achieves competitive quality on unconditioned generation against two baseline models. We also show that our proposed model can generate samples that are twice as long as those produced by the baseline models, and, further, can do so in half the inference time. Moreover, we propose a new measure for analyzing musical self-attentions and show that the trained model learns to pay less attention to notes that form a dissonant interval with the current note, yet attending more to notes that are 4N beats away from current. Finally, our findings provide a novel foundation for future work exploring longer-form multitrack music generation and improving self-attentions for music. All source code and audio samples can be found at https://salu133445.github.io/mtmt/

Large-scale Contrastive Language-Audio Pretraining with Feature Fusion and Keyword-to-Caption Augmentation

Contrastive learning has shown remarkable success in the field of multimodal representation learning. In this paper, we propose a pipeline of contrastive language-audio pretraining to develop an audio representation by combining audio data with natural language descriptions. To accomplish this target, we first release LAION-Audio-630K, a large collection of 633,526 audio-text pairs from different data sources. Second, we construct a contrastive language-audio pretraining model by considering different audio encoders and text encoders. We incorporate the feature fusion mechanism and keyword-to-caption augmentation into the model design to further enable the model to process audio inputs of variable lengths and enhance the performance. Third, we perform comprehensive experiments to evaluate our model across three tasks: text-to-audio retrieval, zero-shot audio classification, and supervised audio classification. The results demonstrate that our model achieves superior performance in text-to-audio retrieval task. In audio classification tasks, the model achieves state-of-the-art performance in the zero-shot setting and is able to obtain performance comparable to models' results in the non-zero-shot setting. LAION-Audio-630K and the proposed model are both available to the public

Prevalence of Avian-Pathogenic Escherichia coli Strain O1 Genomic Islands among Extraintestinal and Commensal E. coli Isolates

Escherichia coli strains that cause disease outside the intestine are known as extraintestinal pathogenic E. coli (ExPEC) and include pathogens of humans and animals. Previously, the genome of avian-pathogenic E. coli (APEC) O1:K1:H7 strain O1, from ST95, was sequenced and compared to those of several other E. coli strains, identifying 43 genomic islands. Here, the genomic islands of APEC O1 were compared to those of other sequenced E. coli strains, and the distribution of 81 genes belonging to 12 APEC O1 genomic islands among 828 human and avian ExPEC and commensal E. coli isolates was determined. Multiple islands were highly prevalent among isolates belonging to the O1 and O18 serogroups within phylogenetic group B2, which are implicated in human neonatal meningitis. Because of the extensive genomic similarities between APEC O1 and other human ExPEC strains belonging to the ST95 phylogenetic lineage, its ability to cause disease in a rat model of sepsis and meningitis was assessed. Unlike other ST95 lineage strains, APEC O1 was unable to cause bacteremia or meningitis in the neonatal rat model and was significantly less virulent than uropathogenic E. coli (UPEC) CFT073 in a mouse sepsis model, despite carrying multiple neonatal meningitis E. coli (NMEC) virulence factors and belonging to the ST95 phylogenetic lineage. These results suggest that host adaptation or genome modifications have occurred either in APEC O1 or in highly virulent ExPEC isolates, resulting in differences in pathogenicity. Overall, the genomic islands examined provide targets for further discrimination of the different ExPEC subpathotypes, serogroups, phylogenetic types, and sequence types

Olfactory perireceptor and receptor events in moths: a kinetic model revised

Modelling reveals that within about 3 ms after entering the sensillum lymph, 17% of total pheromone is enzymatically degraded while 83% is bound to the pheromone-binding protein (PBP) and thereby largely protected from enzymatic degradation. The latter proceeds within minutes, 20,000-fold more slowly than with the free pheromone. In vivo the complex pheromone–PBP interacts with the receptor molecule. At weak stimulation the half-life of the active complex is 0.8 s due to the postulated pheromone deactivation. Most likely this process is enzymatically catalysed; it changes the PBP into a scavenger form, possibly by interference with the C-terminus. The indirectly determined PBP concentration (3.8 mM) is close to direct measurements. The calculated density of receptor molecules within the plasma membrane of the receptor neuron reaches up to 6,000 units per μm2. This is compared with the estimated densities of the sensory-neuron membrane protein and of ion channels. The EC50 of the model pheromone–PBP complex interacting with the receptor molecules is 6.8 μM, as compared with the EC50 = 1.5 μM of bombykol recently determined using heterologous expression. A possible mechanism widening the range of stimulus intensities covered by the dose–response curve of the receptor-potential is proposed

Risk Factors for Stroke During Surgery for Carotid Body Tumors

Vascular Surger