Big issues for small feet : developmental, biomechanical and clinical narratives on children's footwear

The effects of footwear on the development of children's feet has been debated for many years and recent work from the developmental and biomechanical literature has challenged long-held views about footwear and the impact on foot development. This narrative review draws upon existing studies from developmental, biomechanical and clinical literature to explore the effects of footwear on the development of the foot. The emerging findings from this support the need for progress in [children's] footwear science and advance understanding of the interaction between the foot and shoe. Ensuring clear and credible messages inform practice requires a progressive evidence base but this remains big issue in children's footwear research

Fungal invasion of the rhizosphere microbiome

The rhizosphere is the infection court where soil-borne pathogens establish a parasitic relationship with the plant. To infect root tissue, pathogens have to compete with members of the rhizosphere microbiome for available nutrients and microsites. In disease-suppressive soils, pathogens are strongly restricted in growth by the activities of specific rhizosphere microorganisms. Here, we sequenced metagenomic DNA and RNA of the rhizosphere microbiome of sugar beet seedlings grown in a soil suppressive to the fungal pathogen Rhizoctonia solani. rRNA-based analyses showed that Oxalobacteraceae, Burkholderiaceae, Sphingobacteriaceae and Sphingomonadaceae were significantly more abundant in the rhizosphere upon fungal invasion. Metatranscriptomics revealed that stress-related genes (ppGpp metabolism and oxidative stress) were upregulated in these bacterial families. We postulate that the invading pathogenic fungus induces, directly or via the plant, stress responses in the rhizobacterial community that lead to shifts in microbiome composition and to activation of antagonistic traits that restrict pathogen infection

Urbanization and the temporal homogenization of bird communities: a case study in central Argentina

Urban expansion to rural and natural areas is a global process. Although several studies have analyzed bird community attributes along urbanization gradients, little is known on the impact of urbanization on temporal variability of bird communities. Rural areas show higher seasonal and interannual variability in environmental conditions and resources than do urban areas. Our objectives are to determine how seasonal and interannual variability in bird assemblages change along an urban–rural gradient, and how interannual variability in bird assemblages changes with season. Low seasonal and interannual variability of bird communities is expected in urbanized areas that show a process of temporal homogenization. Seasonal variability of bird richness and abundance were positively related to the percent cover of crops. Seasonal and interannual variability in community composition were positively related to coverage of herbaceous vegetation and crops, and negatively related to coverage of impervious areas. Interannual variability of bird richness and abundance were highest during the non-breeding season. We conclude that highly urbanized areas allow bird communities to have a more stable composition over time, promoting temporal homogenization. Our results emphasize that urbanization alters the temporal dynamics of resources and, therefore, the temporal variability of bird communities.Fil: Leveau, Lucas Matias. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Isla, Federico Ignacio. Universidad Nacional de Mar del Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bellocq, Maria Isabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentin

A Supervised Classification Algorithm for Note Onset Detection

This paper presents a novel approach to detecting onsets in music audio files. We use a supervised learning algorithm to classify spectrogram frames extracted from digital audio as being onsets or nononsets. Frames classified as onsets are then treated with a simple peak-picking algorithm based on a moving average. We present two versions of this approach. The first version uses a single neural network classifier. The second version combines the predictions of several networks trained using different hyperparameters. We describe the details of the algorithm and summarize the performance of both variants on several datasets. We also examine our choice of hyperparameters by describing results of cross-validation experiments done on a custom dataset. We conclude that a supervised learning approach to note onset detection performs well and warrants further investigation