Egocentric Perception using a Biologically Inspired Software Retina Integrated with a Deep CNN

We presented the concept of of a software retina, capable of significant visual data reduction in combination with scale and rotation invariance, for applications in egocentric and robot vision at the first EPIC workshop in Amsterdam [9]. Our method is based on the mammalian retino-cortical transform: a mapping between a pseudo-randomly tessellated retina model (used to sample an input image) and a CNN. The aim of this first pilot study is to demonstrate a functional retina-integrated CNN implementation and this produced the following results: a network using the full retino-cortical transform yielded an F1 score of 0.80 on a test set during a 4-way classification task, while an identical network not using the proposed method yielded an F1 score of 0.86 on the same task. On a 40K node retina the method reduced the visual data bye×7, the input data to the CNN by 40% and the number of CNN training epochs by 36%. These results demonstrate the viability of our method and hint at the potential of exploiting functional traits of natural vision systems in CNNs. In addition, to the above study, we present further recent developments in porting the retina to an Apple iPhone, an implementation in CUDA C for NVIDIA GPU platforms and extensions of the retina model we have adopted

Corporate images and customer behavioral intentions in an environmentally certified context: Promoting environmental sustainability in the hospitality industry

Growing environmental awareness has made customers change their attitudes andincreasingly demand that the hospitality industry provides products and services thatare environmentally friendly. This sector faces increasing pressure to operate in amore ecofriendly manner given its negative influence on the natural environment.Extant research demonstrates that sustainable tourism can be promoted throughenvironmental certifications. However, little attention has been paid to the relevanceof customer perceptions about these schemes and their influence on customerbehavioral intentions. So that, this study attempts to explore the conditions underwhich perceived green image leads to favorable customer behavioral intentionstowards environmentally certified hotels by considering the mediating effects offunctional and emotional images. A structured questionnaire was used to collect datafrom hotel customers in Spain. The results indicate that green image serves as apredictor of functional image, which in turn is linked to customer behavioralintentions. This shows that the evaluation of environmental issues influences theassessment of cognitive aspects, although not the direct evaluation of affectiveaspects. Consequently, green image associations directly influence the cognitiveresponses of consumers but not their emotions. Therefore, consumers will evaluatea hotel's functional image not only by considering traditional attributes but also bytaking into account environmental issues. These findings suggest that hotelcompanies should work to develop a green positioning strategy developing productsand services possessing both greenness and high?value attributes

Fc engineered ACE2-Fc is a potent multifunctional agent targeting SARS-CoV2

Joining a function-enhanced Fc-portion of human IgG to the SARS-CoV-2 entry receptor ACE2 produces an antiviral decoy with strain transcending virus neutralizing activity. SARS-CoV-2 neutralization and Fc-effector functions of ACE2-Fc decoy proteins, formatted with or without the ACE2 collectrin domain, were optimized by Fc-modification. The different Fc-modifications resulted in distinct effects on neutralization and effector functions. H429Y, a point mutation outside the binding sites for FcγRs or complement caused non-covalent oligomerization of the ACE2-Fc decoy proteins, abrogated FcγR interaction and enhanced SARS-CoV-2 neutralization. Another Fc mutation, H429F did not improve virus neutralization but resulted in increased C5b-C9 fixation and transformed ACE2-Fc to a potent mediator of complement-dependent cytotoxicity (CDC) against SARS-CoV-2 spike (S) expressing cells. Furthermore, modification of the Fc-glycan enhanced cell activation via FcγRIIIa. These different immune profiles demonstrate the capacity of Fc-based agents to be engineered to optimize different mechanisms of protection for SARS-CoV-2 and potentially other viral pathogens

Effect of brine immersion freezing on the determination of ecological tracers in fish

The use of a multi-ecological tracer approach provides valuable and complementary insights to investigate the complex biology and ecology of large pelagic fish. Brine immersion freezing is the most common preservation technique used onboard for large fish to be frozen whole until they are delivered for sale and processing. We evaluated the effect of brine freezing on lipid and fatty acid composition, C and N stable isotope ratios, and organochlorine contaminant levels of yellowfin tuna (Thunnus albacares) and skipjack tuna (Katsuwonus pelamis). Fresh tunas were stored in a saturated sodium chlorine brine immersion tank maintained at -20 A degrees C for 6 weeks, and ecological tracers were analysed on dorsal muscle samples collected before and after brine freezing. No significant effect of the fish preservation technique was found except for delta N-15 whose signatures slightly increased after a 6-week period of brine immersion. Because N isotopic shift was close to the analytical precision and probably related to a higher risk of salt penetration in small tunas with abraded skin, we consider our results as conservative and conclude that ecological tracers can indeed be analysed on brine-freezing-preserved tunas

The Crowding Out of Complex Social Goods.

The valuation of ecosystem services to inform natural resource management and development has gained acceptance in many arenas. Yet, contemporary economic valuation is constrained to the appraisal of simple goods that generate benefits that accrue to individuals, neglecting complex goods that generate benefits that accrue to society more broadly. Methodological barriers to the valuation of complex social goods have led to their frequent omission from natural resource management deliberations. The prevailing valuation paradigm that focuses on simple individual goods may erode conservation efforts by crowding out the institutions and behaviours that support socially constructed ecosystem service values. Erosion of these values ultimately harms the environment and society as a whole. The institutionalisation of appropriate methods for estimating the value of complex social goods alongside existing methods for valuing simple individual goods within international conservation, development and policy-making discourses, is therefore an important evolution for sustainable natural resource management

Dimeric FcγR ectodomains as probes of the Fc receptor function of anti-influenza virus IgG

Ab-dependent cellular cytotoxicity, phagocytosis, and Ag presentation are key mechanisms of action of Abs arising in vaccine or naturally acquired immunity, as well of therapeutic mAbs. Cells expressing the low-affinity Fc gamma Rs (Fc gamma RII or CD32 and Fc gamma RIII or CD16) are activated for these functions when receptors are aggregated following the binding of IgG-opsonized targets. Despite the diversity of the Fc receptor proteins, IgG ligands, and potential responding cell types, the induction of all Fc gamma R-mediated responses by opsonized targets requires the presentation of multiple Fc regions in close proximity to each other. We demonstrated that such "near-neighbor" Fc regions can be detected using defined recombinant soluble (rs) dimeric low-affinity ectodomains (rsFc gamma R) that have an absolute binding requirement for the simultaneous engagement of two IgG Fc regions. Like cell surface-expressed Fc gamma Rs, the binding of dimeric rsFc gamma R ectodomains to Ab immune complexes was affected by Ab subclass, presentation, opsonization density, Fc fucosylation, or mutation. The activation of an NK cell line and primary NK cells by human IgG-opsonized influenza A hemagglutinin correlated with dimeric rsFc gamma RIIIa binding activity but not with Ab titer. Furthermore, the dimeric rsFc gamma R binding assay sensitively detected greater Fc receptor activity to pandemic H1N1 hemagglutinin after the swine influenza pandemic of 2009 in pooled human polyclonal IgG. Thus these dimeric rsFc gamma R ectodomains are validated, defined probes that should prove valuable in measuring the immune-activating capacity of IgG Abs elicited by infection or vaccination or experimentally derived IgG and its variants

The importance of protecting and conserving the wet Tropics: A synthesis of NERP Tropical Ecosystems Hub tropical rainforest research outputs 2011-2014

This report provides an overview and synthesis of the key findings of research conducted under the Australian Government’s National Environmental Research Program (NERP) Tropical Ecosystems (TE) Hub relevant to tropical rainforests including the Wet Tropics of Queensland World Heritage Area and Cape York. The NERP rainforest research theme comprised ten projects undertaken by researchers from James Cook University, Griffith University, the University of Queensland and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in collaboration with partner agencies. The intent of the NERP funded rainforest research was to improve our understanding of the impacts of future climate change and extreme events on plant and animal biodiversity; gain new insights for beneficial indigenous co-management of protected areas; identify the importance of tourism and community values; determine the status of threatened key indicator species; examine options regarding natural resource management (NRM) governance under greenhouse gas abatement measures; determine the role of fire in the management of the Environment Protection and Biodiversity Conservation (EPBC) Act 1999 listed ecosystems and species; and invasive species management. The research aimed to inform and facilitate management action and remediation to reduce, restore and increase resilience of the Wet Tropics ecosystems. The research findings are also applicable elsewhere, particularly in tropical ecosystems more broadly, but many outcomes can be translated for general application in terrestrial ecosystem management. The report provides an introduction to the Wet Tropics region, a synthesis of key ecological and socio-economic project highlights for the region (including status and trends), future pressures and threats, how research has informed policy and management, and future research priorities.Associated Grant:the Australian Government’s Department of Environmen

Deep Learning with Northern Australian Savanna Tree Species: A Novel Dataset

The classification of savanna woodland tree species from high-resolution Remotely Piloted Aircraft Systems (RPAS) imagery is a complex and challenging task. Difficulties for both traditional remote sensing algorithms and human observers arise due to low interspecies variability (species difficult to discriminate because they are morphologically similar) and high intraspecies variability (individuals of the same species varying to the extent that they can be misclassified), and the loss of some taxonomic features commonly used for identification when observing trees from above. Deep neural networks are increasingly being used to overcome challenges in image recognition tasks. However, supervised deep learning algorithms require high-quality annotated and labelled training data that must be verified by subject matter experts. While training datasets for trees have been generated and made publicly available, they are mostly acquired in the Northern Hemisphere and lack species-level information. We present a training dataset of tropical Northern Australia savanna woodland tree species that was generated using RPAS and on-ground surveys to confirm species labels. RPAS-derived imagery was annotated, resulting in 2547 polygons representing 36 tree species. A baseline dataset was produced consisting of: (i) seven orthomosaics that were used for in-field labelling; (ii) a tiled dataset at 1024 × 1024 pixel size in Common Objects in Context (COCO) format that can be used for deep learning model training; (iii) and the annotations