Designing healthy communities: A walkability analysis of LEED-ND

AbstractPrevailing city design in many countries has created sedentary societies that depend on automobile use. Consequently, architects, urban designers, and land planners have developed new urban design theories, which have been incorporated into the Leadership in Energy and Environmental Design for Neighborhood Development (LEED-ND) certification system. The LEED-ND includes design elements that improve human well-being by facilitating walking and biking, a concept known as walkability. Despite these positive developments, relevant research findings from other fields of study have not been fully integrated into the LEED-ND. According to Zuniga-Teran (2015), relevant walkability research findings from multiple disciplines were organized into a walkability framework (WF) that organizes design elements related to physical activity into nine categories, namely, connectivity, land use, density, traffic safety, surveillance, parking, experience, greenspace, and community. In this study, we analyze walkability in the LEED-ND through the lens of the nine WF categories. Through quantitative and qualitative analyses, we identify gaps and strengths in the LEED-ND and propose potential enhancements to this certification system that reflects what is known about enhancing walkability more comprehensively through neighborhood design analysis. This work seeks to facilitate the translation of research into practice, which can ultimately lead to more active and healthier societies

Nest predation research:Recent findings and future perspectives

Nest predation is a key source of selection for birds that has attracted increasing attention from ornithologists. The inclusion of new concepts applicable to nest predation that stem from social information, eavesdropping or physiology has expanded our knowledge considerably. Recent methodological advancements now allow focus on all three players within nest predation interactions: adults, offspring and predators. Indeed, the study of nest predation now forms a vital part of avian research in several fields, including animal behaviour, population ecology, evolution and conservation biology. However, within nest predation research there are important aspects that require further development, such as the comparison between ecological and evolutionary antipredator responses, and the role of anthropogenic change. We hope this review of recent findings and the presentation of new research avenues will encourage researchers to study this important and interesting selective pressure, and ultimately will help us to better understand the biology of birds

Deep learning predicts function of live retinal pigment epithelium from quantitative microscopy.

Increases in the number of cell therapies in the preclinical and clinical phases have prompted the need for reliable and non-invasive assays to validate transplant function in clinical biomanufacturing. We developed a robust characterization methodology composed of quantitative bright-field absorbance microscopy (QBAM) and deep neural networks (DNNs) to non-invasively predict tissue function and cellular donor identity. The methodology was validated using clinical-grade induced pluripotent stem cell derived retinal pigment epithelial cells (iPSC-RPE). QBAM images of iPSC-RPE were used to train DNNs that predicted iPSC-RPE monolayer transepithelial resistance, predicted polarized vascular endothelial growth factor (VEGF) secretion, and matched iPSC-RPE monolayers to the stem cell donors. DNN predictions were supplemented with traditional machine learning algorithms that identified shape and texture features of single cells that were used to predict tissue function and iPSC donor identity. These results demonstrate non-invasive cell therapy characterization can be achieved with QBAM and machine learning

BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples.

Light-sheet imaging of cleared and expanded samples creates terabyte-sized datasets that consist of many unaligned three-dimensional image tiles, which must be reconstructed before analysis. We developed the BigStitcher software to address this challenge. BigStitcher enables interactive visualization, fast and precise alignment, spatially resolved quality estimation, real-time fusion and deconvolution of dual-illumination, multitile, multiview datasets. The software also compensates for optical effects, thereby improving accuracy and enabling subsequent biological analysis

Use of a polyphasic approach including MALDI-TOF MS for identification of Aspergillus section Flavi strains isolated from food commodities in Brazil

Brazil is one the largest producers and exporters of food commodities in the world. The evaluation of fungi capable of spoilage and the production mycotoxins in these commodities is an important issue that can be of help in bioeconomic development. The present work aimed to identify fungi of the genus Aspergillus section Flavi isolated from different food commodities in Brazil. Thirty-five fungal isolates belonging to the section Flavi were identified and characterised. Different classic phenotypic and genotypic methodologies were used, as well as a novel approach based on proteomic profiles produced by matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS). Type or reference strains for each taxonomic group were included in this study. Three isolates that presented discordant identification patterns were further analysed using the internal transcribed spacer (ITS) region and calmodulin gene sequences. The data obtained from the phenotypic and spectral analyses divide the isolates into three groups, corresponding to taxa closely related to Aspergillus flavus, Aspergillus parasiticus, and Aspergillus tamarii. Final polyphasic fungal identification was achieved by joining data from molecular analyses, classical morphology, and biochemical and proteomic profiles generated by MALDI-TOF MS.Acknowledgments are due to FAPEMIG - Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (Brazil) for financial support. F. C. da Silva extends thanks to CAPES - Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (Brazil) for the PhD grant. C. Santos and N. Lima thank CAPES for the financial support as international visiting professors in the Post-Graduate Programme in Agricultural Microbiology, Federal University of Lavras, Lavras (MG), Brazil

Predation and infanticide influence ideal free choice by a parrot occupying heterogeneous tropical habitats

The ideal free distribution (IFD) predicts that organisms will disperse to sites that maximize their fitness based on availability of resources. Habitat heterogeneity underlies resource variation and influences spatial variation in demography and the distribution of populations. We relate nest site productivity at multiple scales measured over a decade to habitat quality in a box-nesting population of Forpus passerinus (green-rumped parrotlets) in Venezuela to examine critical IFD assumptions. Variation in reproductive success at the local population and neighborhood scales had a much larger influence on productivity (fledglings per nest box per year) than nest site or female identity. Habitat features were reliable cues of nest site quality. Nest sites with less vegetative cover produced greater numbers of fledglings than sites with more cover. However, there was also a competitive cost to nesting in high-quality, low-vegetative cover nest boxes, as these sites experienced the most infanticide events. In the lowland local population, water depth and cover surrounding nest sites were related with F. passerinus productivity. Low vegetative cover and deeper water were associated with lower predation rates, suggesting that predation could be a primary factor driving habitat selection patterns. Parrotlets also demonstrated directional dispersal. Pairs that changed nest sites were more likely to disperse from poor-quality nest sites to high-quality nest sites rather than vice versa, and juveniles were more likely to disperse to, or remain in, the more productive of the two local populations. Parrotlets exhibited three characteristics fundamental to the IFD: habitat heterogeneity within and between local populations, reliable habitat cues to productivity, and active dispersal to sites of higher fitness

Which features of UK farmland are important in retaining territories of the rapidly declining Turtle Dove Streptopelia turtur?

Capsule Turtle Doves continue to show a strong population decline; territories were more likely to be retained in areas with more nesting habitat, and more suitable foraging habitat. Aim To determine which features of farmland in England are important for retaining Turtle Dove territories Methods Fifty-eight grid squares with recent records of territorial Turtle Doves were resurveyed, and squares retaining Turtle Dove territories compared with those from which Turtle Doves had been lost. Results Turtle Dove territories were detected in 48% of squares resurveyed. When correcting for the 70% detection rate of the survey methodology, territories were present in 66% of squares surveyed suggesting a 34% decline over a 2-year period. Established scrub and hedgerows > 4 m tall positively influenced Turtle Dove presence and abundance, as did standing water. Bare ground and fallow had positive effects on Turtle Dove abundance whereas grazed land negatively impacted abundance. Conclusion The positive effects of area of established scrub and volume of large hedgerows are likely to represent a declining density of birds selecting the best quality nest sites. We suggest instead that foraging habitat may be limiting distribution

Living on the edge: utilising lidar data to assess the importance of vegetation structure for avian diversity in fragmented woodlands and their edges

Context: In agricultural landscapes, small woodland patches can be important wildlife refuges. Their value in maintaining biodiversity may, however, be compromised by isolation, and so knowledge about the role of habitat structure is vital to understand the drivers of diversity. This study examined how avian diversity and abundance were related to habitat structure in four small woods in an agricultural landscape in eastern England. Objectives: The aims were to examine the edge effect on bird diversity and abundance, and the contributory role of vegetation structure. Specifically: what is the role of vegetation structure on edge effects, and which edge structures support the greatest bird diversity? Methods: Annual breeding bird census data for 28 species were combined with airborne lidar data in linear mixed models fitted separately at (i) the whole wood level, and (ii) for the woodland edges only. Results: Despite relatively small woodland areas (4.9–9.4 ha), bird diversity increased significantly towards the edges, being driven in part by vegetation structure. At the whole woods level, diversity was positively associated with increased vegetation above 0.5 m and especially with increasing vegetation density in the understorey layer, which was more abundant at the woodland edges. Diversity along the edges was largely driven by the density of vegetation below 4 m. Conclusions: The results demonstrate that bird diversity was maximised by a diverse vegetation structure across the wood and especially a dense understorey along the edge. These findings can assist bird conservation by guiding habitat management of remaining woodland patches